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EP4308719A1 - Combinaisons de biomarqueurs pour des procédés de détection de la trisomie 21 - Google Patents

Combinaisons de biomarqueurs pour des procédés de détection de la trisomie 21

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Publication number
EP4308719A1
EP4308719A1 EP22771947.3A EP22771947A EP4308719A1 EP 4308719 A1 EP4308719 A1 EP 4308719A1 EP 22771947 A EP22771947 A EP 22771947A EP 4308719 A1 EP4308719 A1 EP 4308719A1
Authority
EP
European Patent Office
Prior art keywords
hsa
mir
biomarkers
nucleic acid
combination
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP22771947.3A
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German (de)
English (en)
Other versions
EP4308719A4 (fr
Inventor
Carl Philip Weiner
Yafeng Dong
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Rosetta Signaling Laboratories LLC
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Rosetta Signaling Laboratories LLC
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Filing date
Publication date
Priority claimed from US17/203,534 external-priority patent/US12474355B2/en
Application filed by Rosetta Signaling Laboratories LLC filed Critical Rosetta Signaling Laboratories LLC
Publication of EP4308719A1 publication Critical patent/EP4308719A1/fr
Publication of EP4308719A4 publication Critical patent/EP4308719A4/fr
Pending legal-status Critical Current

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/178—Oligonucleotides characterized by their use miRNA, siRNA or ncRNA

Definitions

  • BIOMARKERS FOR METHODS FOR DETECTING TRISOMY 21 CROSS-REFERENCE TO RELATED APPLICATIONS
  • a human cell has two types of chromosomes. One type is the autosomal chromosomes (chromosomes 1-22), and the other type is the sex chromosome (the X and Y chromosomes). In a normal human cell there are 46 chromosomes, and they are present in the cell as 23 pairs.
  • each normal human cell has two of each autosomal chromosomes (two copies of chromosome 1, two copies of chromosome 2, etc.) and one pair of sex chromosomes (an X and a Y chromosome for a male, or two X chromosomes for a female).
  • a karyotype of a normal male is referred to as 46XY
  • that of a normal female is 46XX.
  • the chromosomal abnormality in a person having trisomy 21 is an extra chromosome 21.
  • the karyotype of a male having trisomy 21 is 47XY+21
  • the karyotype of a female having trisomy 21 is 47XX+21.
  • Trisomy 21 detection methods remain to be developed.
  • a method can include: obtaining a plasma sample from a human subject, wherein the human subject is a pregnant female; obtaining cell free nucleic acids from the plasma sample; detecting in the cell free nucleic acids the presence of a combination of nucleic acid biomarkers comprising: ATP50, ICOSLG, DOP1B, PKNOX1, COL6A1, and GART, wherein the detecting comprises: contacting the cell free nucleic acids with primers or probes that are complementary to the nucleic acid biomarkers in the combination of nucleic acid biomarkers, and detecting hybridization between the primers or probes and the combination of nucleic acid biomarkers.
  • the combination of nucleic acid biomarkers further comprises: ENSG00000199633 F2, hsa-mir-5481, hsa-mir- 26b, hsa-mir-450b and ENSG00000212363.
  • a method can include: obtaining a plasma sample from a human subject, wherein the human subject is a pregnant female; obtaining cell free nucleic acids from the plasma sample; detecting in the cell free nucleic acids the presence of a combination of nucleic acid biomarkers comprising: ENSG00000199633 F2, hsa-mir-5481, hsa-mir-26b, hsa-mir-450b, ENSG00000212363, and GART, wherein the detecting comprises: contacting the cell free nucleic acids with primers or probes that are complementary to the nucleic acid biomarkers in the combination of nucleic acid biomarkers, and detecting hybridization between the primers or probes and the combination of nucleic acid biomarkers.
  • the combination of nucleic acid biomarkers further comprises: ATP50, ICOSLG, DOP1B, PKNOX1, and COL6A1.
  • the combination of nucleic acid biomarkers further comprises: RASGRP4, FAM20A, NEK9, ABCC1, SORBS2; TMPRSS2, DSCAM, ERG, ICOSLG, C21orf33, ADAMTS5, CXADR, NCAM2, UBASH3A, PFKL, CHODL, CYYR1, SLC19A1, PRDM15; COL6A1; and ABCG1.
  • the combination of nucleic acid biomarkers further comprises: ENSG00000199633 F2, ENSG00000207147 F2, hsa-let-7d FI, hsa-mir-569 FI, hsa-mir- 5481, ENSG00000201980, ENSG00000202231, hsa-mir-216b, hsa-mir-98, hsa-mir-26b, hsa- mir-581 FI, hsa-mir-450b, ENSG00000212363, ENSG00000199282, hsa-mir-523, hsa-mir- 376a-2/l F2, ENSG00000199856 FI, and HB 11-276 F2.
  • the nucleic acid biomarkers are RNA.
  • the methods include detecting in the cell free nucleic acids the presence of a normalization nucleic acid.
  • the method includes: obtaining a plasma sample from a second human subject, wherein the second human subject is a pregnant female carrying a fetus without trisomy 21; obtaining a second cell free nucleic acid sample from the plasma sample; and detecting in the second cell free nucleic acid sample the presence of the combination of nucleic acid biomarkers.
  • the method can include: quantitating the amount of each nucleic acid biomarker in the cell free nucleic acids from the pregnant female; and quantitating the amount of each nucleic acid biomarker in the second cell free nucleic acid sample from the second pregnant female.
  • Figures lA-10 Examples of 15 T21 mRNA biomarkers confirmed by Real-time PCR in 10 affected pregnancies.
  • the X-axis is the subject number.
  • the figures represent a graphic illustration of marker expression in trisomy 21 (the squares) compared to the normal range for chromosomally normal fetuses.
  • the dotted lines demarcate the 95% confidence interval for normal.
  • Figures lA-10 are collectively referred to as Figure 1.
  • Figure 2 shows that the maternal age in Normal (euploid fetus) women and those with a Trisomy 21 fetus.
  • Figure 3A shows the Mean RNA expression of a 54 cell free RNAs subset (Group).
  • Figure 3C shows the RNAs found on chromosome #21 are shown.
  • data from the controls was randomly allocated into two groups, then averaged and plotted.
  • the average expression of T21 cases is plotted against the average expression of normal.
  • Figure 3D shows the RNAs found on chromosomes other than # 21.
  • the average expression of the controls is plotted after being randomly allocated into two groups.
  • the T21 cases expression is plotted against average expression of controls.
  • Figures 4A-4I show the ROCs for the 9 RNAs shown by the light dots in Figure 3B with the highest p values.
  • FIG. 4J shows receiver operator characteristic (ROC) curve demonstrates that maternal age was associated with increased T-21 risk, as indicated by the area under the curve (AUC) of 79.6%.
  • Figure 5 shows a comparison of 11 Machine Learning (ML) algorithms.
  • Figure 6 shows general workflow that leads to the identification of the biomarker subsets that are described herein.
  • Figure 7 shows data for the three best performing ML algorithms.
  • Figure 8A shows a specific 6 plasma cell free RNA group that happens to consist of mRNA that are products of genes located on the number 21 chromosome.
  • Figure 8B shows a specific 6 plasma cell free RNA group that consist of 5 small noncoding RNAs produced by genes located on a chromosome other than the number 21, and 1 mRNA that is a product of a gene located on the number 21 chromosome.
  • Figure 8C show a specific 11 plasma cell free RNA group that consists of the 11 unique RNAs identified with C5.0.
  • a method may include screening a fetus for trisomy 21.
  • the method may include measuring a plurality of trisomy 21 biomarkers in a biological sample obtained from a first pregnant female, wherein the plurality of trisomy 21 biomarkers is chosen from any combination of the nucleic acids or a complement thereof.
  • the fetus of the first pregnant female is at least 6 weeks post-implantation, or at least 7 weeks, or at least 8 weeks, or at least 9 weeks, or at least 10 weeks, or at least 12 weeks through the end of pregnancy.
  • the pregnant female may also have a pregnancy that is less than 32 weeks, less than 24 weeks, or less than 18 weeks.
  • the method may also include identifying the fetus as having trisomy 21 if expression of the plurality of biomarkers is altered to a statistically significant degree in the biological sample (e.g., first biological sample) compared to a second biological sample from a second pregnant female carrying a fetus not having trisomy 21.
  • the method may also include identifying the fetus as not having trisomy 21 if expression of the plurality of biomarkers is not altered to a statistically significant degree in the first biological sample compared to a second biological sample from a second pregnant female carrying a fetus not having trisomy 21.
  • expression of a trisomy 21 biomarker is altered to a statistically significant degree if it is outside the 95% confidence interval for that trisomy 21 biomarker.
  • the method may further include recommending a genetic test chosen from amniocentesis, cordocentesis, and chorionic villus sampling or a combination thereof.
  • the plurality of trisomy 21 biomarkers may include at least 6 trisomy 21 biomarkers, wherein the pregnant mother having at least 6 biomarkers whose expression is altered to a statistically significant degree to identify the fetus as having trisomy 21. In one embodiment, the plurality of trisomy 21 biomarkers includes at least 11 trisomy
  • the plurality of trisomy 21 biomarkers may include at least 6 biomarkers, at least 10 biomarkers, at least 11 biomarkers, at least 24 biomarkers, at least 25 biomarkers, at least 27 biomarkers, at least 30 biomarkers, at least 40 biomarkers, at least 43 biomarkers, at least 45 biomarkers, at least 50 biomarkers and at least 54 biomarkers.
  • the groupings of biomarkers described herein can also define the number of biomarkers for analysis in the pregnant mother.
  • the trisomy 21 biomarkers may be selected from polynucleotides encoded by chromosome 21, or from polynucleotides encoded by any of chromosomes 1-20,
  • the trisomy 21 biomarkers may be selected from polynucleotides that are up-regulated in the first pregnant female carrying a fetus with trisomy 21 compared to the second pregnant female carrying a fetus not having trisomy 21. In one embodiment, the trisomy 21 biomarkers may be selected from polynucleotides that are down-regulated in the first pregnant female carrying a fetus with trisomy 21 compared to the second pregnant female carrying a fetus not having trisomy 21.
  • the method may further include obtaining the biological sample from the first pregnant female.
  • the obtaining may include obtaining a blood sample.
  • the blood sample may be processed to remove cells from the blood sample.
  • the blood sample may be processed to obtain, and optionally isolate, cell-free plasma RNA.
  • the method may further include converting RNA polynucleotides present in the biological sample into cDNA molecules, and the measuring includes hybridization between a cDNA molecule and a complementary trisomy 21 biomarker.
  • the complementary trisomy 21 biomarker is in solution during the hybridization, and in one embodiment, the complementary trisomy 21 biomarker is immobilized on a solid support.
  • a method may include detecting trisomy 21 in a fetus.
  • the method may include detecting trisomy 21 biomarkers in a biological sample to yield an expression level of each detected trisomy 21 biomarker in a biomarker combination.
  • the biological sample includes plasma from a pregnant female.
  • the fetus of the first pregnant female is at least 6 weeks post-implantation.
  • the method may also include comparing the expression level of each detected trisomy 21 biomarker in a combination of biomarkers to the expression level of the trisomy 21 biomarker in pregnant females carrying a fetus without trisomy 21.
  • an expression level of a detected trisomy 21 biomarker that is outside the 95% confidence interval for that trisomy 21 biomarker indicates the expression level of the trisomy 21 biomarker is altered.
  • the expression level of the detected trisomy 21 biomarker is determined by application of a machine learning algorithms that analyzes patterns and performs machine ranking.
  • at least 6 or 10 trisomy 21 biomarkers are detected.
  • a fetus carried by the pregnant female is identified as carrying a fetus having trisomy 21 when at least 6 biomarkers are outside the 95% confidence interval.
  • the method may further include recommending a genetic test chosen from amniocentesis, cordocentesis, or chorionic villus sampling.
  • a genetic test chosen from amniocentesis, cordocentesis, or chorionic villus sampling.
  • the pregnant female and the pregnant females used to establish the 95% confidence interval for each trisomy 21 biomarker may be matched with respect to a co- variable such as gestational stage or ethnicity or a combination thereof.
  • the trisomy 21 biomarkers may be selected from polynucleotides encoded by chromosome 21, or from polynucleotides encoded by any of chromosomes 1-20, 22 or X. In one embodiment, the trisomy 21 biomarkers may be selected from polynucleotides that are up-regulated in the pregnant female carrying a fetus with trisomy 21 compared to the pregnant females carrying a fetus not having trisomy 21.
  • the trisomy 21 biomarkers may be selected from polynucleotides that are down- regulated in the pregnant female carrying a fetus with trisomy 21 compared to the pregnant females carrying a fetus not having trisomy 21.
  • the method may further include obtaining the biological sample from the first pregnant female.
  • the obtaining may include obtaining a blood sample.
  • the blood sample may be processed to remove cells from the blood sample.
  • the blood sample may be processed to obtain, and optionally isolate, cell-free plasma RNA.
  • the method may further include converting RNA polynucleotides present in the biological sample into cDNA molecules, and the measuring includes hybridization between a cDNA molecule and a complementary trisomy 21 biomarker.
  • the complementary trisomy 21 biomarker is in solution during the hybridization, and in one embodiment, the complementary trisomy 21 biomarker is immobilized on a solid support.
  • a method may include detecting trisomy 21 in a fetus.
  • the method may include detecting trisomy 21 biomarkers in a biological sample from a pregnant female to yield a sample expression profile.
  • the biological sample includes plasma from a pregnant female.
  • the T21 biomarkers may be chosen from a sequence of (e.g., at least 5, 10, or 15 consecutive) nucleotides selected from any combination of nucleic acid biomarkers as defined herein, or a complement thereof.
  • the fetus of the first pregnant female is greater than 8 weeks post implantation.
  • the method may also include comparing the sample expression profile with a reference expression profile, wherein a difference between the sample expression profile and the reference expression profile is indicative of the presence or absence of trisomy 21 in the fetus.
  • the reference expression profile is from at least one second pregnant female carrying a fetus without trisomy 21, and a difference between the sample expression profile and the reference expression profile is indicative of the presence of trisomy 21.
  • the reference expression profile is from at least one second pregnant female carrying a fetus with trisomy 21, and a difference between the sample expression profile and the reference expression profile is indicative of the absence of trisomy 21.
  • the method may further include recommending a genetic test chosen from amniocentesis, cordocentesis, and chorionic villus sampling.
  • the difference between the sample expression profile and the reference expression profile is statistically significant.
  • the sample expression profile includes at least 6 or 10 trisomy 21 biomarkers.
  • the trisomy 21 biomarkers may be selected from polynucleotides encoded by chromosome 21, or from polynucleotides encoded by any of chromosomes 1-20, 22 or X.
  • the trisomy 21 biomarkers may be selected from polynucleotides that are up-regulated in the first pregnant female carrying a fetus with trisomy 21 compared to the second pregnant female carrying a fetus not having trisomy 21.
  • the trisomy 21 biomarkers may be selected from polynucleotides that are down-regulated in the first pregnant female carrying a fetus with trisomy 21 compared to the second pregnant female carrying a fetus not having trisomy 21.
  • the first pregnant female with a fetus having trisomy 21 and the second pregnant female with a euploid fetus may be matched with respect to a co- variable such as gestational stage and ethnicity.
  • the method may further include obtaining the biological sample from the first pregnant female whose fetus may have trisomy 21.
  • the obtaining may include obtaining a blood sample.
  • the blood sample may be processed to remove cells from the blood sample.
  • the blood sample may be processed to obtain, and optionally isolate, cell-free plasma RNA.
  • the method may further include converting RNA polynucleotides present in the biological sample into cDNA molecules, and the measuring includes hybridization between a cDNA molecule and a complementary trisomy 21 biomarker.
  • the complementary trisomy 21 biomarker is in solution during the hybridization, and in one embodiment, the complementary trisomy 21 biomarker is immobilized on a solid support.
  • an article includes a substrate and a plurality of different polynucleotides.
  • the polynucleotides are selected from any combination nucleic acids as described herein (e.g., defined groups), or a complement thereof.
  • the T21 biomarkers are selected from a sequence of at least 5, 10 or 15 consecutive nucleotides selected from any combination of the nucleic acid biomarkers, or a complement thereof.
  • the polynucleotides are immobilized onto a surface of the substrate.
  • the polynucleotides are immobilized on the substrate surface to form a microarray.
  • at least 10 polynucleotides are immobilized on the substrate surface.
  • kits in one embodiment, includes an article having a substrate, a plurality of different polynucleotides immobilized onto a surface of the substrate, and packaging materials and instructions for use.
  • the polynucleotides are selected from any combination of the defined groups of nucleic acid biomarkers, or a complement thereof.
  • the T21 biomarkers are selected from a sequence of at least 5, 10, or 15 consecutive nucleotides selected from any combination of the defined groups of the nucleic acid biomarkers, or a complement thereof.
  • the polynucleotides are immobilized on the substrate surface to form a microarray.
  • the steps may be conducted in any feasible order. And, as appropriate, any combination of two or more steps may be conducted simultaneously.
  • the methods described herein, and other embodiments disclosed herein such as reagents and kits, are based in part on the surprising discovery of a plurality of molecular markers, the expression levels of which consistently differentiate between healthy subjects and subjects with T21.
  • the molecular markers are derived from coding regions whose altered expression in an affected subject, as measured from an easily obtained biological sample, is indicative of the subject, or the subject’s fetus, having T21.
  • polynucleotide refers to a polymeric form of nucleotides of any length, either ribonucleotides or deoxynucleotides, and includes both double- and single- stranded DNA and RNA.
  • a polynucleotide can be obtained directly from a natural source, or can be prepared with the aid of recombinant, enzymatic, or chemical techniques.
  • a polynucleotide can be linear or circular in topology.
  • cDNA, oligonucleotide, probe, and nucleic acid are included within the definition of polynucleotide and these terms are used interchangeably.
  • polynucleotide also includes peptide nucleic acids (Nielsen et ah, 1991, Science. 254:1497- 500), and other nucleic acid analogs and nucleic acid mimetics (see, e.g., McGall et ah, U.S. Pat. No. 6,156,501).
  • a method provided herein includes detecting one or more T21 biomarkers in a biological sample.
  • a biological sample refers to a sample of tissue or fluid obtained from a subject, including but not limited to, for example, whole blood, blood plasma, serum, lymph fluid, synovial fluid, cerebrospinal fluid, urine, and saliva.
  • a biological sample includes serum.
  • the methods provided herein are directed to non- invasive methods of detecting T21, and in such an embodiment a biological sample may be a fluid.
  • a biological sample includes blood plasma.
  • a biological sample includes whole blood.
  • subject refers to a prenatal or postnatal human.
  • a prenatal human includes a fetus.
  • the term “fetus” refers to a human during prenatal development from the time of first cell division until birth.
  • the fetus may be at any age after implantation.
  • the fetus may be at 2 weeks post-implantation (PI), 4 weeks PI, 6 weeks PI, 8 weeks PI, 10 weeks PI, 12 weeks PI, 14 weeks PI, 16 weeks PI, 18 weeks PI, 20 weeks PI, etc.
  • the fetus is between 6 weeks and 20 weeks PI, or between 7 weeks and 14 weeks PI, or 15-20 weeks PI.
  • a postnatal human refers to an individual at any stage of development after birth, including a newborn, a child, an adolescent, or an adult, and includes a pregnant human mother.
  • the subject is a pregnant human mother
  • the mother does not have T21.
  • a method provided herein allows one to determine if the fetus carried by the pregnant mother has T21.
  • a “T21 biomarker” is a polynucleotide that is indicative of T21 in a subject.
  • a T21 biomarker is indicative of T21 when the expression level or quantity of the biomarker is altered more often in a subject having T21 compared to a healthy subject, which expression level may be higher for a subject having T21 for certain biomarkers, lower for a subject having T21, or in some instances the biomarker may be higher or lower for the subject having T21.
  • the change in the expression level from a standard (e.g., subject without T21) to a statistically significant degree for a combination of biomarkers, whether the change is upregulation or downregulation can provide the indication of T21 in a subject.
  • the same biomarker can increase in one patent but decrease in another patient, but along with the other identified combination of biomarkers, the change itself for that biomarker provides an indication of the subject having T21.
  • a panel or combination of biomarkers can be assessed for a change in expression, and when a certain percentage thereof change expression, whether upregulated or downregulated, the subject is identified as having T21.
  • a T21 biomarker having an altered expression level or quantity is one that is expressed at a greater level (e.g., over-expressed, upregulated) or expressed at a lower level (e.g., under-expressed, downregulated) when compared to a healthy subject or compared against a standard (e.g., average of a plurality of expression profiles for the biomarkers in subjects without T21).
  • a standard e.g., average of a plurality of expression profiles for the biomarkers in subjects without T21.
  • biomarker can, depending on the context, refer to the physical polynucleotide itself or to a graphical or numerical representation of the polynucleotide such as an amount of fluorescence present at a spot on a microarray, a band on a gel image, a numerical value, and the like.
  • the amount of fluorescence at a particular spot on a microarray may be referred to as a T21 biomarker when the fluorescence is linked to a specific polynucleotide.
  • This graphical or numerical biomarker reflects the existence of the underlying expressed polynucleotide in the test sample, which gave rise to an expression level.
  • the detecting of one or more T21 biomarkers in a biological sample yields an expression level of each detected biomarker. In one embodiment, the detecting of two or more T21 biomarkers in a biological sample yields a sample expression profile.
  • An “expression level” is any physical representation of the amount of a selected T21 biomarker, as determined from one or more biological samples from a subject.
  • a “sample expression profile” is any physical representation of the amounts of a set of two or more selected T21 biomarkers, as determined from one or more biological samples from a subject.
  • the subject may be one known to have T21, known to have T21 of a particular type (for instance, 47XX+21, 47XY+21, or mosiac), known to be free of T21, or the status of T21 in the subject may be unknown.
  • a sample expression profile for a subject may include information from a single biological sample that has been analyzed for T21 biomarker expression levels.
  • a sample expression profile for a subject may include information from multiple types of biological samples that have been analyzed separately for T21 biomarker expression levels.
  • normal and healthy are used herein interchangeably to refer to a subject or subjects who do not have a chromosomal abnormality associated with T21.
  • a normal or healthy sample refers to a sample or samples obtained from a normal/healthy subject.
  • the expression level and/or sample expression profile may be represented in visual graphical form, for example on paper or on a computer display, in a three dimensional form such as an array, and/or stored in a computer-readable medium.
  • An expression level and/or sample expression profile may correspond to a particular status of T21 (e.g., presence or absence of T21) or type (e.g., 47XX+21, 47XY+21, or mosiac), and thus provide a template for comparison to a patient sample.
  • a negative control expression level and/or a control expression profile also referred to herein as a reference expression level and a reference expression profile and a standard expression profile, can be obtained by analyzing a biological sample from at least one healthy subject, or multiple samples obtained from a group of healthy subjects.
  • a positive control expression level can be from one or more subjects identified as having comparable T21 in terms of type.
  • the levels of expression of each detected T21 biomarker may be an average, consensus, or composite derived from the multiple samples.
  • comparable profiles can be obtained for age-matched and/or sex-matched subjects, and comparable profiles can be obtained for pregnant mothers at the same or similar stage of pregnancy.
  • expression levels and/or expression profiles can be obtained from a pregnant mother, and if the fetus is later determined to be healthy, such expression levels and/or expression profiles can be used as control expression levels and/or control expression profiles.
  • the median level of each T21 biomarker may be determined at each gestational epoch in control women. If there is a statistically significant change with gestation, regression analysis of median on gestation weighted for the number of samples per epoch may be performed to determine the normal median curve that best fits the data. All results, both affected and unaffected pregnancies, may be expressed as multiples of the gestation- specific median (MoM) based on the fitted curve.
  • MoM gestation- specific median
  • potential co variables may be examined, including maternal weight, smoking, prior preterm birth, diabetes or use of prophylactic progesterone and ethnicity, to see if they are significantly associated with the MoM.
  • other variables such maternal medical diseases
  • Plasma levels of fetal-placental derived sequences may decline on average with increased adiposity due to a fixed output being diluted into a greater volume of blood. If any co-variables are confirmed, the levels can be adjusted by, for instance, dividing the observed MoM by the expected median according to the co variable level found in unaffected pregnancies.
  • the non-parametric Wilcoxon Rank Sum Test is used to select the subset of markers where there is a significant difference in the MoM distribution between affected and control pregnancies.
  • an extreme P-value of 0.005 may be used for an initial selection.
  • the risk of T21 may be modeled by the a priori risk of the disorder expressed as odds (a:b) multiplied by the likelihood ratio (LR) for the marker profile derived from multivariate Gaussian frequency distributions. All current aneuploidy and pre-eclampsia markers follow an approximately log Gaussian distribution over most of their range for both affected and unaffected pregnancies, and it is expected to be true for the T21 biomarkers disclosed herein. In some embodiments, the data may show the distribution is not Gaussian. [These Gaussian distributions are defined by the marker sequence means and standard deviations after log transformation. For a single marker, the LR is calculated by the ratio of the heights of the two overlapping distributions at the specific level.
  • LR For extreme results that fall beyond the point where the data fits a Gaussian distribution, it is standard practice to use the LR at the end of the acceptable range.
  • the method is the same for more than one marker except that the heights of multivariate log Gaussian distributions are used. These are defined, in addition to means and standard deviations, by the correlation coefficients between markers within affected and unaffected pregnancies.
  • machine learning algorithms may be used for analysis, which can include pattern recognition and ranking.
  • the method of numerical integration may be used to model the best combination of markers from the initial subset. This involves division of each marker operating range into up to 100 equal units, calculation of the volumes under the affected and unaffected multivariate Gaussian curves risk as well as the risk in the mid-point of the volume. This determines the distribution of risks in affected and unaffected pregnancies. These distributions will be calculated for all marker combinations and the sensitivity compared for a fixed specificity.
  • a second approach may be considered based on the well-known fact that a strong association does not guarantee effective discrimination between affected and unaffected. Nor does a high AUC guarantee good prediction of actual risk.
  • model calibration via reclassification can be useful in order to accept only those markers least likely to have been identified at random.
  • Prognostic models may be built for predictive accuracy after confirmed T21 with only non-T21 biomarker variables (age, race, maternal weight, gestation age, maternal comorbidities, etc.) and then build prognostic models to include T21 biomarkers. Dimensionality of the models may be reduced by translating the RNA marker contributions into a few components or composite scores. Principal components analysis may be used to derive the principal components of the T21 biomarkers factors.
  • ROC receiver operating characteristic
  • prognostic models can be constructed for T21 status (affected or unaffected) using logistic regression models. Modeling procedures may be similar to those previously described for routinely used Cox models.
  • a T21 biomarker is RNA.
  • the RNA that is detected is cell-free, and is referred to herein as cell-free RNA.
  • Cell-free RNA includes coding RNA (mRNA) and non-coding RNAs such as siRNA, miRNA, snoRNA, piRNA, exRNA, scaRNA, long ncRNAs and snRNA.
  • mRNA coding RNA
  • non-coding RNAs such as siRNA, miRNA, snoRNA, piRNA, exRNA, scaRNA, long ncRNAs and snRNA.
  • cell-free RNA is from whole blood, blood plasma, or serum, and is referred to herein as cell-free plasma (CFP) RNA.
  • CFP RNA includes coding RNA (mRNA) and non-coding RNAs such as, but not limited to, siRNA, miRNA, snoRNA, and snRNA.
  • the CFP RNA to be detected is present in the plasma portion of the blood.
  • a biological sample is processed to remove cells prior to the detecting.
  • a biological sample is processed to minimize cell lysis.
  • the CFP RNA that is detected may be mRNA, non-coding RNA, or the combination thereof.
  • the CFP RNA may be isolated.
  • RNA may be obtained from a biological sample using routine methods.
  • RNA is obtained using a process based on a phenol/guanidium isothiocyanate/glycerol phase separation.
  • Such a process may result in large quantities of CFP nucleic acid with total RNA yields of 8-30 ug or more from only 2 mL of plasma and full range of RNAs including not only mRNA but also small noncoding RNAs such as miRNA and snoRNA. This amount is more than enough for both array and RNAseq technologies and the performance of numerous PCR reactions using a clinically practical, single patient sample.
  • RNA isolation method described herein allows for the isolation of 8 micrograms to 30 micrograms of CFP RNA from a 2 mL sample, which is more than enough for both microaarray gene screening and PCR validation.
  • the method may include obtaining 2 mL or more of sample from a subject, such as plasma, and following the steps as described in Example 1.
  • T21 biomarkers are described at SEQ ID NO:8-3,273. Different combinations of the T21 biomarkers listed at SEQ ID NO:8-3,273, or the complement thereof, allow the skilled person to predict whether the fetus carried by a pregnant mother has T21.
  • the panel of T21 biomarkers includes a subset encoded by chromosome 21 (e.g., SEQ ID NOs: 3,028-3,065 and 3,238). That subset includes polynucleotides found to be up- regulated in a pregnant mother carrying a fetus that is T21 when compared to a pregnant mother carrying a normal fetus. That subset also includes polynucleotides found to be down- regulated in a pregnant mother carrying a fetus that is T21 when compared to a pregnant mother carrying a normal fetus.
  • the panel of biomarkers includes a subset encoded by chromosomes other than chromosome 21, e.g., chromosomes 1-20, 22, and/or x (e.g., SEQ ID NOs:8-3,027, 3,066- 3,227 and 3,239-3,248).
  • That subset includes polynucleotides found to be up-regulated in a pregnant mother carrying a fetus that is T21 when compared to a pregnant mother carrying a normal fetus.
  • That subset also includes polynucleotides found to be down-regulated in a pregnant mother carrying a fetus that is T21 when compared to a pregnant mother carrying a normal fetus.
  • the panel of T21 biomarkers includes a subset that are mRNAs (e.g., SEQ ID NO:8- 3,250) and a subset that are small non-coding RNAs (SEQ ID NO:3, 251-3, 248).
  • An expression level of a T21 biomarker may include polynucleotide expression level information for one polynucleotide chosen from SEQ ID NO: 8-3,248, obtained from a biological sample from a subject.
  • a sample expression profile may include polynucleotide expression level information for two or more polynucleotides chosen from SEQ ID NO:8-3,2473 or 8-3,273, obtained from a biological sample from a subject, for instance, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, at least 21, at least 22, at least 23, at least 24, at least 25, at least 26, at least 27, at least 28, at least 29, or at least 30.
  • a sample expression profile may include polynucleotide expression level information for no greater than 30 polynucleotides chosen from SEQ ID NO:8-3,273, obtained from a biological sample from a subject, for instance, no greater than 30, no greater than 29, no greater than 28, no greater than 27, no greater than 26, no greater than 25, no greater than 24, no greater than 23, no greater than 22, no greater than 21, no greater than 20, no greater than 19, no greater than 18, no greater than 17, no greater than 16, no greater than 15, no greater than 14, no greater than 13, no greater than 12, no greater than 11, no greater than 10, no greater than 9, no greater than 8, no greater than 7, no greater than 6, or no greater than 5.
  • a nucleotide sequence used in a method provided herein is of a length that is at least substantially unique for a T21 biomarker to specifically hybridize with a RNA, such as a CFP RNA, present in a biological sample.
  • a nucleotide sequence used in a method provided herein may be RNA, DNA, or RNA/DNA hybrid.
  • a T21 biomarker present in a biological sample may be a polynucleotide that contains or consists of the sequence which defines the T21 biomarker target or complement thereof, or associated RNA or DNA thereof.
  • the T21 biomarker may be identical to one of SEQ ID NOs:8-3,248 or 8-3,273, or can be a complement thereof, sense or antisense, as well as a sequence that hybridizes therewith under suitable conditions.
  • the biomarker When provided as a DNA sequence, the biomarker also includes the corresponding RNA sequence.
  • the biomarker When provided as an RNA sequence, the biomarker also includes the corresponding DNA sequence.
  • a T21 biomarker used to detect a RNA present in a biological sample may be at least 6, at least 15, at least 20, at least 25, at least 30, at least 35, or at least 40 nucleotides in length, and so on, of a sequence selected from SEQ ID NO: 8-3,273, or the complement thereof.
  • a T21 biomarker may include a sequence selected from SEQ ID NO: 8-3,273, or the complement thereof, that is from 10 nucleotides to the full sequence, from 16 nucleotides to 100 nucleotides, from 17 nucleotides to 50 nucleotides, from 18 nucleotides to 30 nucleotides, from 19 nucleotides to 25 nucleotides, or from 20 to 22 nucleotides.
  • a T21 biomarker selected from SEQ ID NO: 8- 3,273 may have perfect identity, at least 95% identity, at least 90% identity, at least 85% identity, or at least 80% identity with a sequence disclosed herein.
  • a T21 biomarker selected from SEQ ID NO: 8-3,273 may have perfect complementarity or at least 95% complementarity, at least 90% complementarity, at least 85% complementarity, or at least 80% complementarity with a sequence disclosed herein.
  • a T21 biomarker may be continuous or it can have one or more bulges or mismatches upon hybridization.
  • a T21 biomarker used to detect a RNA in a biological sample may also include one or more chemical modifications, such as a 2’ carbon modification.
  • a T21 biomarker may or may not form an overhang upon hybridization when detecting a RNA present in a biological sample.
  • Hybridization includes any process by which a strand of a nucleic acid sequence joins with a second nucleic acid sequence strand through base-pairing. Hybridization of polynucleotides is affected by such conditions as salt concentration, temperature, or organic solvents, in addition to the base composition, length of the complementary strands, and the number of nucleotide base mismatches between the hybridizing nucleic acids, as will be readily appreciated by those skilled in the art. Stringency conditions depend on the length and base composition of the nucleic acid, which can be determined by techniques well known in the art. Generally, stringency can be altered or controlled by, for example, manipulating temperature and salt concentration during hybridization and washing.
  • a combination of high temperature and low salt concentration increases stringency.
  • the degree of stringency may be based, for example, on the calculated (estimated) melting temperature (T m ) of the polynucleotide. Calculation of T m is well known in the art. For example, “maximum stringency” typically occurs at around T m -5°C (5° below the T m of the probe); “high stringency” at around 5-10° below the T m ; “intermediate stringency” at around 10-20° below the T m of the probe; and “low stringency” at around 20-25° below the T m .
  • Maximum stringency conditions may be used to identify a polynucleotide present in a biological sample having strict identity or near-strict identity with a T21 biomarker selected from SEQ ID NO: 8-3,248 or 8-3,273; while high stringency conditions are used to identify a polynucleotide present in a biological sample having about 80% or more sequence identity with a T21 biomarker.
  • T21 biomarker selected from SEQ ID NO: 8-3,248 or 8-3,273
  • high stringency conditions are used to identify a polynucleotide present in a biological sample having about 80% or more sequence identity with a T21 biomarker.
  • Such conditions are known to those skilled in the art and can be found in, for example, Strauss, W. M. "Hybridization With Radioactive Probes," in Current Protocols in Molecular Biology 6.3.1-6.3.6, (John Wiley & Sons, N.Y. 2000). Both aqueous and nonaqueous conditions as described in the art
  • Expression levels of any one or more of the T21 biomarkers described herein may be used to determine the presence, absence, or type of T21 in a subject.
  • expression levels of one or more T21 biomarkers encoded by chromosome 21 may be used to determine the presence, absence, or type of T21 in a subject.
  • expression levels of one or more T21 biomarkers encoded by the remaining 21 autosomes (chromosomes 1-22 exclusive of chromosome 21) and X may be used to determine the presence, absence, or type of T21 in a subject.
  • expression levels of one or more T21 biomarkers encoded by any combination of chromosomes 1-22 and X may be used to determine the presence, absence, or type of T21 in a subject. In one embodiment, expression levels of one or more T21 biomarkers encoded by one chromosome selected from 1-22 and X may be used to determine the presence, absence, or type of T21 in a subject.
  • expression levels of one or more T21 biomarkers that are mRNAs may be used to determine the presence, absence, or type of T21 in a subject.
  • expression levels of one or more T21 biomarkers that are small non-coding RNAs may be used to determine the presence, absence, or type of T21 in a subject.
  • the T21 biomarkers used may be those that are up-regulated in a pregnant mother carrying a fetus that is T21 when compared to a pregnant mother carrying a normal fetus.
  • the T21 biomarkers used may be those that are down-regulated in a in a pregnant mother carrying a fetus that is T21 when compared to a pregnant mother carrying a normal fetus. In one embodiment, the T21 biomarkers used may be a combination of those that are up- regulated and those that are down-regulated in a pregnant mother carrying a fetus that is T21 when compared to a pregnant mother carrying a normal fetus.
  • T21 biomarkers used in an assay to determine the presence, absence, or type or T21 in a subject may vary. The skilled person will appreciate that, generally, the more biomarkers examined, the more accurate the determination of the presence, absence, or type of T21 in a subject; however, the skilled person will also appreciate that there is a minimum number of biomarkers useful for an accurate diagnosis of T21.
  • the number of T21 biomarkers evaluated in practicing a method provided herein may be at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, at least 21, at least 22, at least 23, at least 24, at least 25, at least 26, at least 27, at least 28, at least 29, or at least 30.
  • the number of T21 biomarkers evaluated in practicing a method provided herein may be no greater than 30, no greater than 29, no greater than 28, no greater than 27, no greater than 26, no greater than 25, no greater than 24, no greater than 23, no greater than 22, no greater than 21, no greater than 20, no greater than 19, no greater than 18, no greater than 17, no greater than 16, no greater than 15, no greater than 14, no greater than 13, no greater than 12, no greater than 11, no greater than 10, no greater than 9, no greater than 8, no greater than 7, no greater than 6, or no greater than 5.
  • the number of CFP RNAs detected varies depending upon whether the fetus or subject is normal or abnormal. However, the number can be the same as in a group defined herein.
  • All the T21 biomarkers measured in a subject having T21 may not show altered expression levels when compared to a healthy subject.
  • a subject may be considered to have T21 when at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, or 100% of the T21 biomarkers in a sample expression profile from the subject’s biological sample show altered expression when compared to those T21 biomarkers in a negative control expression profile from a healthy subject.
  • the subject may be considered to have T21 when at least 6 of the biomarkers in a sample expression profile show altered expression when compared to those T21 biomarkers in a control expression profile from a healthy subject.
  • Some of the T21 biomarkers in a subject not having T21 may show altered expression levels when compared to another healthy subject.
  • a subject may be considered not to have T21 when no greater than 40%, no greater than 35%, no greater than 30%, no greater than 25%, no greater than 20%, no greater than 15%, no greater than 10%, no greater than 5%, or none of the T21 biomarkers in a sample expression profile from the subject’s biological sample show altered expression when compared to those T21 biomarkers in a control expression profile from another healthy subject.
  • the subject may be considered to have a normal fetus when no more than 4 of the biomarkers in a sample expression profile show altered expression when compared to the normal range for the population of healthy fetuses.
  • Whether the expression level or quantity of a biomarker in a subject having T21 is greater than or less than the expression level or quantity of the biomarker in a healthy subject is determined using routine statistical methods by applying accepted confidence levels.
  • the expression level or quantity of a T21 biomarker in a biological sample is considered to be altered if the difference in amount of the biomarker in a test sample is increased or decreased to a statistically significant degree compared to the amount of the biomarker in a control sample.
  • the term “statistically significant” refers to a result, namely a difference in numbers of positive results between a test and a control that is not likely due to chance.
  • the minimum chance level for statistical significance herein is 95% probability that the result is not due to chance, i.e., random variations in the data.
  • a 95% confidence interval means that if the procedure for computing a 95% confidence interval is used over and over, 95% of the time the interval will contain the true parameter value.
  • the minimum chance level for statistical significance is 97% probability, 99% probability, or 99.9% probability.
  • Various methods, as is known, can be used to calculate statistical significance. Examples include, but are not limited to, binomial probabilities, the Poisson distribution, chi-square, and t-test.
  • a subject is considered to have T21 when comparison of expression of at least one T21 biomarker, or a plurality of T21 biomarkers, with the expression level of the at least one T21 biomarker, or a plurality of T21 biomarkers, in a biological sample from a subject not having T21 shows a difference, and that difference is indicative of the presence of T21 in the subject.
  • a subject is considered to have T21 when expression of at least one T21 biomarker, or a plurality of T21 biomarkers, is altered to a statistically significant degree or determined by machine learning in a biological sample from the subject compared to a biological sample from a subject not having trisomy 21.
  • a subject is considered to have T21 when comparison of expression of at least one T21 biomarker with the expression level of the at least one T21 biomarker in a biological sample from a subject not having T21 shows that the expression level or quantity of a biomarker in the subject is outside the 95% confidence interval for the biomarker.
  • a subject is considered to have T21 when comparison of expression of a plurality of T21 biomarkers with the expression level of the plurality of T21 biomarkers in a biological sample from a subject not having T21 shows that the expression level or quantity of the plurality of biomarker in the subject is outside the 95% confidence interval for the plurality of the biomarkers.
  • a method provided herein includes measuring a plurality of T21 biomarkers in a biological sample obtained from a subject, such as a pregnant female.
  • the plurality of T21 biomarkers (e.g., a specific combination) measured may be selected from any combination of a defined group, or a complement thereof, or a portion thereof.
  • the plurality of T21 biomarkers measured may be polynucleotides that hybridize to a sequence selected from any one of SEQ ID NO:8-3,273 under suitable conditions.
  • a method provided herein includes detecting T21 biomarkers in a biological sample to yield an expression level of each detected T21 biomarker.
  • the T21 biomarkers may be selected from any combination of SEQ ID NO:8-3,273, or a complement thereof, or a portion thereof.
  • the T21 biomarkers detected may be polynucleotides that hybridize to a sequence selected from any one of SEQ ID NO:8-3,273 under suitable conditions.
  • the biological sample may include plasma from a pregnant female.
  • a method disclosed herein includes detecting T21 biomarkers in a biological sample to yield a sample expression profile.
  • the T21 biomarkers may be selected from any combination of SEQ ID NO:8-3,273, or a complement thereof, or a portion thereof.
  • the T21 biomarkers detected may be selected from SEQ ID NO:8-3,273, or a complement thereof, or a portion thereof.
  • the T21 biomarkers detected may be polynucleotides that hybridize to a sequence selected from any one of SEQ ID NO:8-3,273 under suitable conditions.
  • the biological sample may include plasma from a pregnant female.
  • a method disclosed herein may include identifying the fetus as i) having trisomy 21 if expression of the plurality of biomarkers is altered to a statistically significant degree in the biological sample compared to a biological sample from a second pregnant female carrying a fetus not having trisomy 21, or ii) not having trisomy 21 if expression of the plurality of biomarkers is not altered to a statistically significant degree in the biological sample compared to a biological sample from a second pregnant female carrying a fetus not having trisomy 21.
  • the method may further include comparing the expression level of a detected T21 biomarker to the expression level of the T21 biomarker in pregnant females carrying a fetus without T21, wherein an expression level of a detected T21 biomarker that is outside the 95% confidence interval for that T21 biomarker indicates the expression level of the T21 biomarker is altered.
  • the method may further include comparing the sample expression profile with a reference expression profile; wherein a difference between the sample expression profile and the reference expression profile is indicative of the presence of trisomy 21 in the fetus. A sample whose expression levels were not different from the standard control would be interpreted to be from a pregnancy unaffected by T21. A significant difference from the standard would lead to the conclusion T21 was present.
  • a method may further include recommending to the pregnant female a genetic test chosen from amniocentesis, cordocentesis, and chorionic villus sampling.
  • Amounts of T21 biomarkers in a biological sample may be determined in absolute or relative terms. If expressed in relative terms, amounts can be expressed as normalized amounts with reference to one or more normalization sequences present in a biological sample. It is expected that this method will have a sensitivity (percent of fetuses or subjects having T21 correctly identified, also referred to as detection rate) of at least 98%, at least 99%, or 100% when enough T21 biomarkers present in a biological sample are detected. It is also expected that this method will have a specificity (percent of fetuses or subjects not having T21 correctly identified) of at least 98%, at least 99%, or 100% when enough T21 biomarkers present in a biological sample are detected.
  • RNA may be obtained from a biological sample using routine techniques known in the art.
  • the RNA is cell-free RNA obtained from biological tissue and/or fluid.
  • the RNA is cell-free plasma RNA obtained from whole blood, blood plasma, or serum.
  • the RNA is isolated.
  • isolated refers to a polynucleotide that has been removed from its natural environment.
  • Detecting one or more T21 biomarkers that are present as a RNA polynucleotide may be accomplished by a variety of methods. Some methods are quantitative and allow estimation of the original levels of RNA between the levels present in a test sample and a control, such as a control expression level for a T21 biomarker and/or a control expression profile, whereas other methods are merely qualitative.
  • a method for detecting one or more T21 biomarkers may include the use of polynucleotides that are in solution, and may be in any format, including, but not limited to, the use of individual tubes or a high throughput device, such as a PCR-card.
  • Quantitative real-time PCR may be used to measure the differential expression of any T21 biomarker in a test sample and a control.
  • the RNA template is generally reverse transcribed into cDNA, which is then amplified via a PCR reaction.
  • the primers used for amplification may be selected by determining which T21 biomarker(s) described at SEQ ID NO:8-3,273 is to be amplified, and then designing primers using routine methods known in the art.
  • the PCR amplification process is catalyzed by a thermostable DNA polymerase.
  • thermostable DNA polymerases include Taq DNA polymerase, Pfu DNA polymerase, Tli (also known as Vent) DNA polymerase, Tfl DNA polymerase, and Tth DNA polymerase.
  • the PCR process may include three steps (i.e., denaturation, annealing, and extension) or two steps (i.e., denaturation and annealing/extension).
  • the temperature of the annealing or annealing/extension step may vary, depending upon the amplification primers and other parameters such as concentration.
  • the temperature of the annealing or annealing/extending step may range from about 50°C to about 75°C.
  • the amount of PCR product is followed cycle-by-cycle in real time, which allows for determination of the initial concentrations of mRNA.
  • the reaction may be performed in the presence of a dye that binds to double-stranded DNA, such as SYBR Green.
  • the reaction may also be performed with fluorescent reporter probes, such as TAQMAN probes (Applied Biosystems, Foster City, Calif.) that fluoresce when the quencher is removed during the PCR extension cycle. Fluorescence values are recorded during each cycle and represent the amount of product amplified to that point in the amplification reaction.
  • the cycle when the fluorescent signal is first recorded as statistically significant is the threshold cycle (Ct).
  • Ct threshold cycle
  • QRT-PCR is typically performed using one or more normalization sequences.
  • Reverse-transcriptase PCR may also be used to measure the expression of a T21 biomarker.
  • the RNA template is reverse transcribed into cDNA, which is then amplified via a typical PCR reaction. After a set number of cycles the amplified DNA products are typically separated by gel electrophoresis. Comparison of the relative amount of PCR product amplified in different samples will reveal whether the expression of a T21 biomarker is altered in a test sample. Accordingly, sequences in the Sequence Listing showing DNA can have the “T” replaced with a “U” to convert to the corresponding RNA, and vice versa.
  • Expression of a T21 biomarker may also be measured using a nucleic acid microarray (also referred to in the art as a DNA chip or biochip).
  • a nucleic acid microarray also referred to in the art as a DNA chip or biochip.
  • single-stranded polynucleotides selected from at least a portion of SEQ ID NO:8-3,273, or a complement thereof are plated, or arrayed, on a solid support.
  • the solid support may be a material such as, for instance, glass, silica-based, silicon-based, a synthetic polymer, a biological polymer, a copolymer, a metal, or a membrane.
  • the form or shape of the solid support may vary, depending on the application.
  • Suitable examples include, but are not limited to, slides, strips, plates, wells, microparticles, fibers (such as optical fibers), gels, and combinations thereof.
  • the arrayed immobilized sequences are generally hybridized with specific DNA probes obtained from the test sample.
  • RNA present in a sample including T21 biomarkers, is generally reverse transcribed into cDNA.
  • Fluorescently labeled cDNA probes may be generated through incorporation of fluorescently labeled deoxynucleotides during the reverse transcription step.
  • the cDNA probes are hybridized to the immobilized nucleic acids on the solid support under highly stringent conditions.
  • the solid support is scanned using routine methods, for instance, by confocal laser microscopy or by another detection method, such as a CCD camera. Quantitation of hybridization of each arrayed element allows for assessment of corresponding RNA abundance. With multiple color fluorescence, separately labeled cDNA probes may be hybridized pairwise to the array. The relative abundance of the transcripts from the two sources corresponding to each specified T21 biomarker may then be determined simultaneously. Microarray analysis may be performed by commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GenChip technology, or Incyte's microarray technology.
  • RNA samples are first separated by size via electrophoresis in an agarose gel under denaturing conditions. The RNA is then transferred to a membrane, crosslinked, and hybridized, under highly stringent conditions, to a labeled DNA probe. After washing to remove the non-specifically bound probe, the hybridized labeled species are detected using routine techniques known in the art.
  • the probe may be labeled with, for instance, a radioactive element, a chemical that fluoresces when exposed to ultraviolet light, a tag that is detected with an antibody, or an enzyme that catalyses the formation of a colored or a fluorescent product.
  • a comparison of the relative amounts of RNA detected in a control sample and a test sample will reveal whether the expression of one or more T21 biomarkers or changed in the test sample.
  • Nuclease protection assays may also be used to monitor the altered expression of a T21 biomarker in a test sample and a control.
  • an antisense probe hybridizes in solution to a RNA sample.
  • the antisense probe may be labeled with an isotope, a fluorophore, an enzyme, or another tag.
  • nucleases are added to degrade the single-stranded, unhybridized probe and RNA.
  • An acrylamide gel is used to separate the remaining protected double- stranded fragments, which are then detected using techniques well known in the art. Again, qualitative differences in expression may be detected.
  • expression of a T21 biomarker may be e amined in vivo in a subject.
  • One or more RNA polynucleotides may be labeled with fluorescent dye, a bioluminescent marker, a fluorescent semiconductor nanocrystal, or a short-lived radioisotope, and then the subject may be imaged or scanned using a variety of techniques, depending upon the type of label.
  • the detection of a RNA uses the nucleotides of a specific exon as described in SEQ ID NO:8-3,273.
  • the primers used to amplify the CFP RNA will amplify all or a portion of an exon described in SEQ ID NO:8-3,273.
  • the arrayed immobilized sequence used to detect the CFP RNA will be based on all or a portion of an exon described in SEQ ID NO:8-3,273, or a complement thereof.
  • a person skilled in the art will know which parameters may be manipulated to optimize detection of a RNA of interest using one or more of the polynucleotides listed at SEQ ID NO:8-3,273.
  • a normalization sequence is a polynucleotide that can be used to normalize the relative amounts of polynucleotides, and/or data obtained from the polynucleotides, from one sample to the next.
  • a normalization sequence can be RNA that has an expression level or quantity that is generally stable under the conditions studied.
  • the normalization sequence can have an expression level or quantity that is substantially unaffected by physiological circumstances present in a subject, and thus the normalization sequence can be used to normalize the amount of polynucleotides in separate samples for comparison.
  • the separate samples can be from different subjects or the same subject at different time points, such as different time points in pregnancy.
  • the normalization sequence can be used to normalize the amount of RNA in QRT-PCR studies, such as by normalizing the amount of a RNA sequence of interest.
  • the normalization sequences described herein can be used alone or in combination and may be used to normalize samples to be assayed for T21 biomarkers.
  • the normalization sequences provided herein can be for quantification of cell-free RNA, including CFP RNA, present in a biological sample.
  • RNA e.g., mRNA: 18s RNA, RPLPO, and GAPDH; miRNA: miR-103, miR-146a, and miR-197) were either expressed inconsistently in control plasma samples or were altered by either pregnancy, gestational age or disease (see Dong and Weiner, WO 12/075150, incorporated by reference).
  • the normalization sequences described can include cell-free plasma RNA sequences (including coding sequences, e.g., mRNA, and/or non-coding sequences, e.g., miRNA) that are substantially unchanged by a condition. In one embodiment, the normalization sequences are substantially unchanged during the course of pregnancy.
  • the normalization sequence includes a circulating RNA.
  • a normalization sequence can be described as human (i.e., Homo sapiens ) peptidylprolyl isomerase A (i.e., cyclophilin A, rotmase A), which is encoded by a PPIA coding region.
  • the normalization sequence can be an mRNA for peptidylprolyl isomerase.
  • An example of a peptidylprolyl isomerase normalization sequence can be found at accession number: NM_021130 and/or NM_001008741.
  • a peptidylprolyl isomerase normalization sequence that may be useful for normalization of mRNA is depicted at SEQ ID NO: 1.
  • the normalization sequence may include miRNA.
  • Such a normalization sequence may be a Drosophila melanogaster small nuclear RNA, such as snRNA:U6.
  • the snRNA:U6 normalization sequence can be snRNA:U6 at 96Aa, 96:Ab, and/or 96Ac.
  • SEQ ID NO: 2 for miRNA
  • snRNA:U6:96Ab SEQ ID NO: 3 for miRNA
  • snRNA:U6:96Ac SEQ ID NO: 4 for miRNA
  • SEQ ID NO: 4 for miRNA
  • SEQ ID NO: 4 for miRNA
  • SEQ ID NO: 4 for miRNA
  • SEQ ID NO: 4 for miRNA
  • SEQ ID NO: 4 for miRNA
  • SEQ ID NO:l may be used for normalization of mRNA
  • SEQ ID NOs: 2-4 may be used for normalization of miRNA. More than one normalization sequence may be used.
  • sequences for the forward primer, reverse primer, and probe for SEQ ID NO:l may be: Forward primer: GCTTTGGGTCCAGGAATGG (SEQ ID NO:5); Reverse primer: GTTGTCCACAGTCAGCAATGGT (SEQ ID NO: 6); and Probe:
  • a normalization sequence may be a polynucleotide that contains or consists of the sequence.
  • the normalization sequence can be identical to one of SEQ ID NO: 1-7, or can be a complement thereof, sense or antisense, as well as a sequence that hybridizes therewith under suitable conditions.
  • a normalization sequence may include a sequence selected from SEQ ID NO: 1-7, or the complement thereof, that is at least 15 nucleotides, at least 20 nucleotides, at least 25 nucleotides, at least 30 nucleotides, at least 35 nucleotides, at least 40 nucleotides, at least 45 nucleotides, at least 50 nucleotides, or at least 55 nucleotides, to the full sequence.
  • the normalization sequence can include a sequence of SEQ ID NO:l, 2, 3, 4, 5, 6, or 7.
  • a normalization sequence may have perfect identity, at least 95% identity, at least 90% identity, at least 85% identity, or at least 80% identity with a sequence selected from SEQ ID NO: 1-7.
  • a normalization sequence may have perfect complementarity or at least 95% complementarity, at least 90% complementarity, at least 85% complementarity, or at least 80% complementarity with a sequence selected from SEQ ID NO: 1-7.
  • a normalization sequence may be continuous or it can have one or more bulges or mismatches upon hybridization.
  • a normalization sequence may also include one or more chemical modifications, such as a 2’ carbon modification.
  • a normalization sequence may or may not form an overhang upon hybridization when detecting a RNA present in a biological sample.
  • an article that includes a substrate and a plurality of individual polynucleotides.
  • the individual polynucleotides may be selected from SEQ ID NO:8-3,273, or a complement thereof, or a portion thereof.
  • the polynucleotides are immobilized onto a surface of the substrate. In one embodiment, the polynucleotides are immobilized on the substrate surface to form a microarray.
  • kits may include one or more polynucleotides for measuring the expression of at least one T21 biomarker, wherein alteration in the expression of the one or more T21 biomarkers in a subject relative to a control is indicative of the presence, absence, or type of T21.
  • a kit may include one or more polynucleotides that are specific to a selected T21 biomarker
  • a polynucleotide present in a kit may have a sequence that is identical to a polynucleotide listed at SEQ ID NO:8-3,273, or the complement thereof.
  • polynucleotide present in a kit may have a portion of a sequence that is identical to a polynucleotide listed at SEQ ID NO:8-3,273, or the complement thereof.
  • the polynucleotides to be used in the measurement of the expression of one or more T21 biomarkers can, depending upon the type of technique to be used.
  • the kit may include polynucleotides useful as primers for QRT-PCR.
  • Polynucleotides useful as probes may be included in a kit and are optionally provided together with a solid substrate, such as but not limited to a bead, a chip, a plate, and a microarray. Polynucleotides may be immobilized on the surface of such a substrate.
  • a kit may also further include a reverse transcriptase, a thermostable DNA polymerase, appropriate buffers and salts, or the combination thereof.
  • kits may further include one or more additional reagents such as, but not limited to, buffers such as amplification buffers, hybridization buffers, labeling buffers, or any equivalent reagent.
  • additional reagents such as, but not limited to, buffers such as amplification buffers, hybridization buffers, labeling buffers, or any equivalent reagent.
  • Reagents may be supplied in solid (e.g., lyophilized) or liquid form, and these may optionally be provided in individual packages using containers such as vials, packets, bottles and the like, for each individual reagent.
  • Each component can for example be provided in an amount appropriate for direct use or may be provided in a reduced or concentrated form that can be reconstituted.
  • a kit may further include materials and tools useful for carrying out methods described herein.
  • a kit can be used for example in diagnostic laboratories, clinical settings, or research settings.
  • the kit may further include instructions for use, including for example any procedural protocols and instructions for using the various reagents in the kit for performing different steps of the process.
  • Instructions for using the kit according to one or more methods of the invention may include instructions for processing a biological sample obtained from a subject and/or for performing the test, and instructions for analyzing or interpreting the results. Instructions may be provided in printed form or stored on any computer readable medium including but not limited to DVDs, CDs, hard disk drives, magnetic tape and servers capable of communicating over computer networks.
  • a kit may further include one or more normalization sequences.
  • a method of detecting a combination of nucleic acid biomarkers in a human subject can include: obtaining a nucleic acid sample from the human subject; selecting the combination of nucleic acid biomarkers; analyzing a transcriptome of the human subject for the combination of nucleic acid biomarkers in the nucleic acid sample from the human subject; detecting in the nucleic acid sample the presence of the combination of nucleic acid biomarkers, wherein each nucleic acid biomarker in the combination of nucleic acid biomarkers has a variation from a transcription standard.
  • the method includes providing the transcription standard for each nucleic acid biomarker for the combination of nucleic acid biomarkers.
  • the method includes providing the combination of nucleic acid biomarkers as a set of primers and/or probes.
  • the method includes obtaining cell free plasma RNA as the nucleic acid sample.
  • the nucleic acid biomarkers are RNA.
  • the method can include generating a report, the report reciting the presence of the combination of nucleic acid biomarkers being present in the nucleic acid sample of the human subject being present in a biomarker amount that is varied from the transcription standard.
  • a kit in one embodiment, includes purified or isolated nucleic acids, wherein the nucleic acids have the sequences of each of the nucleic acid biomarkers in the combination of biomarkers. As such, each recited combination can be uniquely included in a kit.
  • the nucleic acid biomarkers are attached to a substrate of a biochip, where each nucleic acid biomarker can be in a unique position or a position can include one or more of the nucleic acid biomarkers of the combination.
  • nucleic acid biomarker or “biomarker” is defined to be a nucleic acid, such as an RNA, that is present in an abnormal amount compared to a standard or normal amount. The biomarker thereby then serves as a tool to look for changes in the transcription thereof. For example, a biomarker can be present at a normal or standard level when there is no disease state or susceptibility of a disease state, but the biomarker is present at a changed level or a variation from the standard or normal amount.
  • the nucleic acid biomarkers described herein may always be present, but the change in the transcription thereof or change in the amount or concentration in blood or plasma provides the indication that the subject may have a condition that is marked by the biomarker.
  • biomarker it is clear that the transcription thereof, amount thereof or concentration thereof is not normal, such that it is changed.
  • Such a changed condition can be compared to subject (e.g., pregnant woman, fetus possibly having T21 whether known or unknown) prior to pregnancy or in early pregnancy (e.g., earlier than 12 weeks or between 16-20 weeks).
  • a biomarker it is defined that the transcription thereof, amount thereof or concentration thereof is detectably different from a standard or normal person without the condition or the same subject prior to onset of the condition - T21 in the fetus.
  • a biomarker requires at least a fold change relative to the normal or standard amount or concentration or transcription, or at least a 1.3 fold change, or at least a 1.4 fold change, or at last a 1.5 fold change, or at least a 1.6 fold change, or at least a 1.7 fold change, whether the change is up regulation (increased transcription, amount or concentration) or down regulation (decreased transcription, amount or concentration) compared to a standard or normal amount or compared to that of the subject prior to being pregnant or prior to 9 weeks or prior to 12 weeks of gestation (or prior to 7 weeks or prior to 10 weeks implantation).
  • “combination of biomarkers” or “combination of nucleic biomarkers” defines a unique combination of nucleic acids that are biomarkers under the definition of a biomarker provided herein.
  • the combination of biomarkers provides an indication of a T21 disease state in a fetus of a pregnant woman.
  • the combination of biomarkers can be detected to be present in a biomarker amount by hybridizing the biomarker with a biomarker primer (PCR) or biomarker probe (biochip).
  • the combination of biomarkers can be calculated or quantitated with a normalization nucleic acid during the detection of the biomarker amount thereof.
  • the combination of biomarkers can be tied to a disease state - T21 of a fetus. Once the disease state is identified for the combination of biomarkers, a treatment regimen can be provided to the subject, such as pregnant woman or the fetus thereof, that has the biomarker amount. In one aspect, a further confirmatory diagnostic protocol can be performed to confirm T21.
  • the treatment regimen can then be implemented on the pregnant woman, such as providing a report with the information of abortion as an option or choosing to end the pregnancy.
  • the combination of biomarkers can be present as a kit in the combination.
  • the kit may include instructions identifying the combination of biomarkers and the indication of the disease state thereof.
  • Transcriptome-typing can be performed with the combination of biomarkers. Transcriptome-typing is equivalent to genotyping for transcribed RNA.
  • a method for detecting T21 in an asymptomatic subject comprising: (a) subjecting a sample from the subject to a procedure to detect polynucleotides (biomarkers) of specific Groups; (b) detecting T21 by comparing the amount of polynucleotides in a specific biomarker group to the amount of such polynucleotides obtained from a control who does not have T21 wherein the polynucleotides comprise at least one of, or are selected from Group 1, 2, 3, 4, 5, or combination groups thereof, or any other combination of groups described herein.
  • a method where the procedure comprises detecting Groups of polynucleotides in the sample by contacting the sample with oligonucleotides that hybridize to the polynucleotides (biomarkers); and detecting in the sample levels of nucleic acids that hybridize to the polynucleotides relative to a control, wherein a change or significant difference in the amount or status of the polynucleotides in the sample compared with the amount or status in the control is indicative of T21.
  • a method wherein the procedure comprises: contacting the sample with the group of biomarkers that specifically bind to the polynucleotides under conditions effective to bind the biomarkers and form complexes; measuring the amount or status of the polynucleotides present in the sample by quantitating the amount of the complexes; and wherein a change or significant difference in the amount or status of polynucleotides in the sample compared with the amount or status obtained from a control subject who does not suffer from T21 is indicative of T21.
  • the amount of polynucleotides that are RNA are detected via polymerase chain reaction using, for example, oligonucleotide primers that hybridize to one or more combinations of biomarkers, or complements of such combinations of biomarkers.
  • the amount of RNA is detected using a hybridization technique, employing oligonucleotide probes that hybridize to one or more combinations of biomarkers, or complements thereof.
  • FIG. 2 shows that the maternal age in Normal (euploid fetus) women and those with a Trisomy 21 fetus.
  • the Normal controls e.g., birth of euploid baby at term, included five self-identified racial and ethnic groups: White (698, 73%), Black (144, 15%), South Asian (48, 5%), East Asian (24, 2.5%), and mixed (37, 3.9%).
  • the “cases” e.g., birth of a T21 baby, included 3 self- identified racial and ethnic groups: White (42, 86%), Black (6, 12%) and East Asian (2, 4%). Due to the imbalanced dataset, “race” was excluded as a predictor variable for ML.
  • the gestational age at sampling of the T21 group was higher by an average of 0.3 wk compared to control, but the range was the same 11.2-14.1 wks (Table 2).
  • Both the maternal height and weight varied significantly among racial and ethnic groups (not shown), but did not differ between T21 cases and Normal controls.
  • the box illustrates the median and the 25th-75 percentile range.
  • the solid circles show the number of women whose age was above the 90th or below the 10th percentile.
  • This data illustrates the well-known increase in Trisomy 21 prevalence with advancing maternal age. This shows that the risk of Trisomy 21 (T-21) increases with maternal age, where the maternal age of the T21 cases was significantly different (older) than the healthy controls.
  • Asterisk indicates p ⁇ 0.05 Mann-Whitney-Wilcoxon test, two tails.
  • the box and whisker plot in A the box indicates the range from first through third quartiles, and the line in the box indicates the median.
  • the whiskers indicate the 10 and 90 th percentile ranges, and the filled circles indicate potential outliers.
  • Figures 3A-3B show that the protocols provide for high reproducibility of the high throughput assay that is utilized for gene quantification and the differential plasma cell free RNA expression in women with a Trisomy 21 fetus.
  • Figure 3A shows the Mean RNA expression of a 54 cell free RNAs subset (Group) from the original list of 3,248 plasma cell free RNA markers. This group of 54 cell free RNAs is selected because they had the highest differential expression half in women with a Trisomy 21 fetus. One half of the Normal subjects were selected at random and mean expression for each RNA marker was plotted against the mean expression of the same marker in the second half of Normal women. The solid line represents the correlation between the two groups.
  • the light dots identify the 10 variables with the highest p values for differential expression in women with a Trisomy 21 fetus by Mann Whitney U test after adjustment by a Bonferroni correction.
  • the solid line between the dashed lines represents the correlation illustrated on the right, while the solid line that crosses the dashed lines is the correlation between the T21 and Normal groups. Notice the change in slope, which indicates the change obtained with the selected group of 54 cell free RNAs. Averaged expression data from the 50 T21 cases was plotted against averaged expression data from the 948 controls.
  • Figure 3C shows the RNAs found on chromosome #21.
  • data from the controls was randomly allocated into two groups, then averaged and plotted.
  • the average expression of T21 cases is plotted against the average expression of normal.
  • the line fitting this data and the 95% confidence interval is shown.
  • the solid black lines show the regression fit for control vs. control (the broken lines indicate the 95% confidence interval).
  • the solid grey lines show the regression fit for T21 vs control (the broken lines indicate the 95% confidence interval).
  • the numbers next to the data points of T21 vs control indicate the RNA identification found in the plate.
  • Figure 3D shows the RNAs found on chromosomes other than # 21.
  • the average expression of the controls is plotted after being randomly allocated into two groups.
  • the T21 cases expression is plotted against average expression of controls.
  • FIGS 4A-4I show the ROCs for the 9 RNAs shown by the light dots in Figure 3B with the highest p values. These are a specific subset grouping of the cell free RNAs. Boxplots and receiver operator characteristic (ROC) curves for the nine differentially expressed RNAs following Bonferroni correction for false discovery rate.
  • ROC receiver operator characteristic
  • RNAs are plotted individually to show differential expression and a ROC curve.
  • PCR RNA from an independent and more diverse patient cohort than used in Discovery phase indicates validation of 9-15 RNAs originally suggested by microarray / qPCR as being differentially expressed between T21 case and Normal control
  • AUC indicates that the predictive power of each of the 9 differentially expressed RNAs falls in a “fair” 0.6-0.7 range, similar to what was found modeling Maternal Age, alone (see Figure 2).
  • FIG. 4J shows the receiver operator characteristic (ROC) curve demonstrates that maternal age was associated with increased T-21 risk, as indicated by the area under the curve (AUC) of 79.6%.
  • ROC receiver operator characteristic
  • FIG. 5 shows a comparison of 11 Machine Learning (ML) algorithms: Gradient Boosting Machine (GBM), C5.0, Random Forest (FR), Adaboost, Naive Bayesian (NB), Earth, Mean Decrease in Accuracy (MDA), linear discriminant analysis (LDA), Neural Network (NNET), Support Vector Machine (SVM), and Classification and Regression Trees (CART).
  • GBM and C5.0 proved superior for the detection of Trisomy 21 fetuses with RF close behind using all 54 plasma cell free RNA markers in terms of accuracy and Kappa.
  • GBM gradient boosting machine
  • C50 classification of data and decision tree algorithm C5.0
  • RF random forest
  • adaboost a decision tree model that uses a boosting method to improve learning rate
  • NB naive Bayes, a classification method that is based on Bayes’ Theorem
  • Earth multivariate adaptive regression splines model
  • MDA flexible discriminant analysis
  • LDA linear discriminant analysis
  • NNET neural network
  • SVM support vector machine
  • CART classification and regression trees.
  • Figure 6 shows general workflow that leads to the identification of the biomarker subsets that are described herein.
  • the workflow uses artificial intelligence to select the biomarker groups described herein, and the selected biomarker groups can be used in the multiple models in order to identify women whose fetus had/have Trisomy 21.
  • Figure 6 shows the effect of training partition size and class imbalance on three machine learning algorithms: Random Forest, C5.0, and GBM, which shows the workflow.
  • Random Forest C5.0
  • GBM which shows the workflow.
  • the dataset was randomly partitioned into training and testing (evaluation) sets from 45% of the data allocated to training, up to 90% of the data.
  • four different methods were applied that rebalance the class size. Specifically, Oversampling, which randomly adds to the minority group with repetition to parity; Down sampling, which randomly eliminates from the majority group to parity; or using ROSE or SMOTE, which are synthetic methods that created equal size groups using different approaches.
  • ROSE or SMOTE which are synthetic methods that created equal size groups using different approaches.
  • three models, Random Forest, C5.0 or GMB were trained using 10-fold cross validation with 5 repeats, then the performance of each model was evaluated using the holdout dataset.
  • Figure 7 shows data for the three best performing ML algorithms. The data shows the impact on partitioning whether the protocol uses oversample, down sample, Rose or Smote. Oversampling in each instance provided the highest model Kappa and Accuracy with the optimal performance somewhere between 70-80%.
  • Figures 8A-8C shows that the group of 54 plasma cell free RNA markers were tested for the prediction of Trisomy 21 using C5.0 with bagging. The RNAs utilized in the best performing C5.0 models were then entered into Random Forest, and the diagnostic models of Figures 8A-8C resulted.
  • Figure 8A shows a specific 6 plasma cell free RNA group that happens to consist of mRNA that are products of genes located on the number 21 chromosome.
  • the model’s accuracy is diagnostic of Trisomy 21.
  • a specific group of the 6 plasma cell free RNA is provided for diagnostics: ATP50; ICOSLG; DOPEY2; PKNOX1; COL6A; and GART.
  • Figure 8B shows a specific 6 plasma cell free RNA group that consist of 5 small noncoding RNAs produced by genes located on a chromosome other than the number 21, and 1 mRNA that is a product of a gene located on the number 21 chromosome.
  • the model’s accuracy is diagnostic of Trisomy 21.
  • a specific group of the 6 plasma cell free RNA group is provided for diagnostics: ENSG00000119633; miR-548i; miR-26b; miR-450b; EN S G00000212363 ; and GART.
  • Figure 8C show a specific 11 plasma cell free RNA group that consists of the 11 unique RNAs identified with C5.0.
  • the model’s accuracy is diagnostic of Trisomy 21.
  • a specific group of the 11 plasma cell free RNA group is provided for diagnostics: ATP50; ICOSLG; DOPEY2; PKNOX1; COL6A; GART; ENSG00000119633; miR-548i; miR-26b; miR-450b; and ENSG00000212363.
  • the nucleic acid biomarkers can be useful because they can be detected as a combination of nucleic biomarkers in a human subject. This detected combination of biomarkers when detected to have transcription levels that are outside of normal transcriptional levels provides information about the probability of defined heath scenarios. For example, the specific combinations of the nucleic acid biomarkers having the variation from the transcriptional standard can be used for assessing the likelihood of trisomy 21. Accordingly, methods are described herein for detecting the combination of nucleic biomarkers.
  • the combination of biomarkers being upregulated or downregulated provide an indication that the subject pregnant female carries a fetus having trisomy 21.
  • the results of the combination of biomarkers can be obtained, and the variation for each detected to be: no variation; an upregulation; or a downregulation.
  • a report can be generated to identify the variation of each biomarker in the combination, and the results thereof relative to the patient being sampled for the biomarker combination.
  • the report can further provide a recommendation for further medical evaluations to confirm whether or not the presence of the combination of nucleic acid biomarkers was a true positive result or a false positive result.
  • the presence of the combination of biomarkers can provide an indication of the corresponding fetus having T21, and the report can provide recommendations of specific medical protocols for confirming whether or not the indication is true or false.
  • the methods may also include the performance of the subsequent medical procedure to confirm the indication to be true or false, whereby a report can be generated regarding the indication by the presence of the combination of biomarkers compared to the outcome or results of the subsequent medical procedure.
  • a method of detecting a combination of nucleic acid biomarkers in a human subject can include: obtaining a nucleic acid sample from the human subject; analyzing a transcriptome of the human subject for the combination of nucleic acid biomarkers in the nucleic acid sample from the human subject; selecting the combination of nucleic acid biomarkers; detecting in the nucleic acid sample the presence of the combination of nucleic acid biomarkers, wherein each nucleic acid biomarker in the combination of nucleic acid biomarkers has a variation from a transcription standard, wherein the combination of nucleic acid biomarkers includes: ATP50 having a nucleotide sequence of or complementary to SEQ ID NO: 3249; ICOSLG having a nucleotide sequence of or complementary to SEQ ID NO: 3265; DOP1B (also known as DOPEY2) having a nucleotide sequence of or complementary to SEQ ID NO: 3250; PKNOX1 having a nucleotide sequence of or
  • the combination of nucleic acid biomarkers includes: ATP50 having a nucleotide sequence of or complementary to SEQ ID NO: 3249 with a transcriptional variation that is downregulated compared to the transcription standard; ICOSLG having a nucleotide sequence of or complementary to SEQ ID NO: 3265 with a transcriptional variation that is downregulated compared to the transcription standard; DOP1B having a nucleotide sequence of or complementary to SEQ ID NO: 3250 with a transcriptional variation that is downregulated compared to the transcription standard; PKNOX1 having a nucleotide sequence of or complementary to SEQ ID NO: 3254 with a transcriptional variation that is upregulated compared to the transcription standard; COL6A1 having a nucleotide sequence of or complementary to
  • the combination of nucleic acid biomarkers is: ENSG00000199633 F2 having a nucleotide sequence of or complementary to SEQ ID NO: 3217; hsa-mir-5481 having a nucleotide sequence of or complementary to SEQ ID NO: 3165; hsa-mir-26b having a nucleotide sequence of or complementary to SEQ ID NO: 3161; hsa- mir-450b having a nucleotide sequence of or complementary to SEQ ID NO: 3246; ENSG00000212363 having a nucleotide sequence of or complementary to SEQ ID NO: 3170; and GART having a nucleotide sequence of or complementary to SEQ ID NO: 3256.
  • Table 2 shows this combination of nucleic acid biomarkers - Group 2 - as a defined panel where each must be present and detected for a variation of no variation; an upregulation; or a downregulation.
  • the combination of nucleic acid biomarkers is: ENSG00000199633 F2 having a nucleotide sequence of or complementary to SEQ ID NO: 3217 with a transcriptional variation that is upregulated compared to the transcription standard; hsa-mir-5481 having a nucleotide sequence of or complementary to SEQ ID NO: 3165 with a transcriptional variation that is downregulated compared to the transcription standard; hsa-mir-26b having a nucleotide sequence of or complementary to SEQ ID NO: 3161 with a transcriptional variation that is downregulated compared to the transcription standard; hsa-mir-450b having a nucleotide sequence of or complementary to SEQ ID NO: 3246 with a transcriptional variation that is downregulated compared to the transcription standard; and ENSG00000212363 having a nucleotide sequence of or complementary to SEQ ID NO: 3170 with a variation less than the transcription standard; and GART having a nucleotide sequence of or complementary
  • the combination of nucleic acid biomarkers is: ATP50 having a nucleotide sequence of or complementary to SEQ ID NO: 3249; ICOSLG having a nucleotide sequence of or complementary to SEQ ID NO: 3265; DOP1B having a nucleotide sequence of or complementary to SEQ ID NO: 3250; PKNOX1 having a nucleotide sequence of or complementary to SEQ ID NO: 3254; COL6A1 having a nucleotide sequence of or complementary to SEQ ID NO: 3272; and GART having a nucleotide sequence of or complementary to SEQ ID NO: 3256.
  • Table 3 shows this combination of nucleic acid biomarkers - Group 3 - as a defined panel where each must be present and detected for a variation of no variation; an upregulation; or a downregulation.
  • the combination of nucleic acid biomarkers is: ATP50 having a nucleotide sequence of or complementary to SEQ ID NO: 3249 with a transcriptional variation that is downregulated compared to the transcription standard; ICOSLG having a nucleotide sequence of or complementary to SEQ ID NO: 3265 with a transcriptional variation that is downregulated compared to the transcription standard; DOP1B having a nucleotide sequence of or complementary to SEQ ID NO: 3250 with a transcriptional variation that is downregulated compared to the transcription standard; PKNOX1 having a nucleotide sequence of or complementary to SEQ ID NO: 3254 with a transcriptional variation that is upregulated compared to the transcription standard; COL6A1 having a nucleotide sequence of or complementary to SEQ ID NO: 3272 with a transcriptional variation that is downregulated compared to the transcription standard; and GART having a nucleotide sequence of or complementary to SEQ ID NO: 3256 with a transcriptional variation that is downregulated compared to
  • the combination of nucleic acid biomarkers in Group 1 further comprises a sub-group of biomarkers (A) to form Group 1A, which Group 1A includes the biomarkers of Group 1 and the following additional sub-group (A) of mRNA biomarkers: RASGRP4 having a nucleotide sequence of or complementary to SEQ ID NO: 3257; FAM20A having a nucleotide sequence of or complementary to SEQ ID NO: 3258;
  • NEK9 having a nucleotide sequence of or complementary to SEQ ID NO: 3259; ABCC1 having a nucleotide sequence of or complementary to SEQ ID NO: 3260; SORBS2 having a nucleotide sequence of or complementary to SEQ ID NO: 3261; TMPRSS2 having a nucleotide sequence of or complementary to SEQ ID NO: 3262; DSCAM having a nucleotide sequence of or complementary to SEQ ID NO: 3263; ERG having a nucleotide sequence of or complementary to SEQ ID NO: 3264; ICOSLG having a nucleotide sequence of or complementary to SEQ ID NO: 3265; C21orf33 having a nucleotide sequence of or complementary to SEQ ID NO: 3266; ADAMTS5 having a nucleotide sequence of or complementary to SEQ ID NO: 3267; CXADR having a nucleotide sequence of or complementary to SEQ ID NO: 3268; PFKL having
  • the combination of nucleic acid biomarkers in Group 1 further comprises a sub-group of biomarkers to form Group 1A, which Group 1A includes the biomarkers of Group 1 and the following additional biomarkers: RASGRP4 having a nucleotide sequence of or complementary to SEQ ID NO: 3257 with a transcriptional variation that is downregulated compared to the transcription standard; FAM20A having a nucleotide sequence of or complementary to SEQ ID NO: 3258 with a transcriptional variation that is downregulated compared to the transcription standard; NEK9 having a nucleotide sequence of or complementary to SEQ ID NO: 3259 with a transcriptional variation that is downregulated or upregulated compared to the transcription standard; ABCC1 having a nucleotide sequence of or complementary to SEQ ID NO: 3260 with a transcriptional variation that is upregulated compared to the transcription standard; SORBS2 having a nucleotide sequence of or complementary to SEQ ID NO: 3261 with a transcriptional variation that
  • COL6A1 having a nucleotide sequence of or complementary to SEQ ID NO: 3272 with a transcriptional variation that is downregulated compared to the transcription standard
  • ABCG1 having a nucleotide sequence of or complementary to SEQ ID NO: 3273 with a transcriptional variation that is downregulated compared to the transcription standard.
  • the combination of nucleic acid biomarkers in Group 1 further comprises a second sub-group (B) of biomarkers to form Group IB, which Group IB includes the biomarkers of Group 1 and the following additional biomarkers (B) sub group (B) are small non-coding RNA that can include: ENSG00000199633 F2 having a nucleotide sequence of or complementary to SEQ ID NO: 3217; ENSG00000207147 F2 having a nucleotide sequence of or complementary to SEQ ID NO: 3238; hsa-let-7d FI having a nucleotide sequence of or complementary to SEQ ID NO: 3189; hsa-mir-569 FI having a nucleotide sequence of or complementary to SEQ ID NO: 3163; hsa-mir-5481 having a nucleotide sequence of or complementary to SEQ ID NO: 3165; ENSG00000201980 having a nucleotide sequence of or complementary to SEQ
  • sub-group (B) are small non-coding RNA that can include: ENSG00000199633 F2 having a nucleotide sequence of or complementary to SEQ ID NO: 3217 with a transcriptional variation that is upregulated compared to the transcription standard; ENSG00000207147 F2 having a nucleotide sequence of or complementary to SEQ ID NO: 3238 with a transcriptional variation that is upregulated compared to the transcription standard; hsa-let-7d FI having a nucleotide sequence of or complementary to SEQ ID NO: 3189 with a transcriptional variation that is upregulated compared to the transcription standard; hsa-mir-569 FI having a nucleotide sequence of or complementary to SEQ ID NO: 3163 with a transcriptional variation that is downregulated compared to the transcription standard; hsa-mir-5481 having a nucleotide sequence of or complementary to SEQ ID NO: 3165 with a transcriptional variation that is downregulated compared to the transcription standard;
  • hsa-mir-98 having a nucleotide sequence of or complementary to SEQ ID NO: 3245 with a transcriptional variation that is downregulated compared to the transcription standard
  • hsa-mir-26b having a nucleotide sequence of or complementary to SEQ ID NO:
  • hsa-mir-581 FI having a nucleotide sequence of or complementary to SEQ ID NO: 3173 with a transcriptional variation that is upregulated compared to the transcription standard
  • hsa-mir-450b having a nucleotide sequence of or complementary to SEQ ID NO: 3246 with a transcriptional variation that is downregulated compared to the transcription standard
  • ENSG00000212363 having a nucleotide sequence of or complementary to SEQ ID NO: 3170 with a transcriptional variation that is downregulated compared to the transcription standard
  • ENSG00000199282 having a nucleotide sequence of or complementary to SEQ ID NO: 3207 with a transcriptional variation that is downregulated compared to the transcription standard
  • hsa-mir-523 having a nucleotide sequence of or complementary to SEQ ID NO: 3233 with a transcriptional variation that is downregulated compared to the transcription standard
  • the combination of nucleic acid biomarkers in Group 1 further comprises the first sub-group of biomarkers (A) and the second sub-group of biomarkers (B) to form Group 1C of biomarkers, which Group 1C includes the RNA biomarkers of Group 1 and the first sub-group (A) mRNA biomarkers and the sub-group (B) of small non-coding RNA biomarkers.
  • Group 1A characterized with sub-group D results in Group 1AD.
  • Group 1C characterized with the sub-group D results in Group 1 and Group 1CD.
  • the Group 1 of Table 1 can have one or more of the biomarkers being a specific examples of the combination of nucleic acid biomarkers - Group 1 - as a defined panel where each must be present and detected for a variation of no variation; an upregulation; or a downregulation.
  • Group 1 can be specified in the following example: ATP50 including ATP5O-Hs04272738_ml with a transcriptional variation that is downregulated compared to the transcription standard; ICOSLG including ICOSLG-Hs00391287_ml with a transcriptional variation that is downregulated compared to the transcription standard; DOP1B including DOP1B-Hs01123288_ml with a transcriptional variation that is downregulated compared to the transcription standard; PKNOX1 including PKNOX1-Hs01007092_ml with a transcriptional variation that is upregulated compared to the transcription standard; COL6A1 including COL6A1-Hs01095585_ml with a transcriptional variation that is downregulated compared to the transcription standard; and GART including GART-Hs00531926_ml with a transcriptional variation that is downregulated compared to the transcription standard.
  • the recited biomarkers in any of the groups can include the sample in
  • any of the groups of biomarkers having GART can be specified as having the following example of GART including GART-Hs00531926_ml with a transcriptional variation that is downregulated compared to the transcription standard.
  • the combination of nucleic acid biomarkers further comprises: FAM20A including FAM20A-Hs01034071_ml that is downregulated compared to the transcriptional standard, and FAM20A-Hs01034070_m that is downregulated compared to the transcriptional standard; NEK9 including NEK9-Hs00929602_ml that is downregulated compared to the transcriptional standard, and NEK9-Hs00929594_m that is upregulated compared to the transcriptional standard; SORBS2 including SORBS2-Hs01125202_ml that is upregulated compared to the transcriptional standard and SORBS2-Hs00243432_ml that is downregulated compared to the transcriptional standard; DOP1B including DOP1B- Hs01123288_ml that is downregulated compared to the transcriptional standard and DOP1B- Hs01123267_gl that is downregulated compared to the transcriptional standard; UBASH3A including UBASH3A-
  • the combination of nucleic acid biomarkers includes or consists of: RASGRP4-Hs01073179_ml; FAM20A-Hs0103407 l_ml; FAM20A- Hs01034070_ml; NEK9-Hs00929602_ml; NEK9-Hs00929594_ml; ABCC1- Hs01561504_ml; SORBS2-Hs01125202_ml; SORBS2-Hs00243432_ml; TMPRSS2-ERG fusion gene; ATP5O-Hs04272738_ml; DSCAM-Hs00242097_ml; ERG-Hs01573964_ml; ICOSLG-Hs00391287_ml; DOP1B-Hs01123288_ml; DOP1B-Hs01123267_gl; C21orf33- Hs01105802_gl;
  • Hs00953342_ml SLC19A1-Hs00953341_ml; PRDM15-Hs00411318_ml; COL6A1-
  • Hs01095585_ml ABCG1-Hs01555191_ml; GART-Hs00531926_ml; ENSG00000199633 F2; ENSG00000207147 F2; hsa-let-7d FI; hsa-mir-569 FI; hsa-mir-5481;
  • the method of using the combination of nucleic acid biomarkers includes hybridizing each nucleic acid biomarker in the nucleic acid sample with a complementary nucleic acid configured as a primer or a probe, the method comprising detecting the hybridizing.
  • a combination of primers forward and/or reverse
  • a combination of probes e.g., labeled, bound to substrate, etc.
  • the method can include providing the transcription standard for each nucleic acid biomarker for the combination of nucleic acid biomarkers. That is, each biomarker in each combination has a transcription standard across populations without T21.
  • the biological sample of the pregnant mother can be assayed for the combination of nucleic acid biomarkers of one of the Groups to see whether the pregnant woman has the combination of biomarkers in that Group varying from the transcriptional standard.
  • the presence of the combination of biomarkers having the variation from the transcription standard provide for the indication that the fetus of the pregnant mother has T21.
  • the method can include obtaining cell free plasma RNA as the nucleic acid sample, wherein the nucleic acid biomarkers are RNA (e.g., having RNA nucleic acids).
  • the method can include generating a report, the report reciting the presence of the combination of nucleic acid biomarkers being present in the nucleic acid sample of the human subject being present in a biomarker amount that is varied from the transcription standard.
  • the report can include any of the information provided herein, such as the presence of the combination of nucleic acid biomarkers having the deviation from the transcriptional standard, what such a presence of the Group of biomarkers means for the fetus, and a listing of further medical procedures and actions recommended or options to be taken.
  • the combination of nucleic acid biomarkers is the combination defined as Group 4, shown in Table 4. Table 4 shows this combination of nucleic acid biomarkers - Group 4 - as a defined panel where each must be present and detected for a variation of no variation; an upregulation; or a downregulation.
  • the combination of nucleic acid biomarkers is the combination defined as Group 5, shown in Table 5.
  • Table 5 shows this combination of nucleic acid biomarkers - Group 5 - as a defined panel where each must be present and detected for a variation of no variation; an upregulation; or a downregulation.
  • the present invention includes a method of determining a primer or a probe for a CFP RNA biomarker.
  • a method of determining a primer or a probe for a CFP RNA biomarker can include analyzing one or more of the sequences of the Sequence Listing or Figures and determining a unique or sufficiently unique specific target sequence that is useful as a primer or a probe therefore.
  • the primers can be readily determined from the sequences of the sequence listing by convention techniques, and may encompass low stringency, medium stringency and high stringency primers, and thereby the primer sequences that are useful can be changed within the sequences provided in the Sequence Listing.
  • the CFP RNA biomarkers can be used to indicate whether or not a fetus of a pregnant woman has T21. This determination can be performed by a blood test at least as early as 10 weeks gestation. Accordingly, the biomarkers identified herein can be combined in a mathematical algorithm that can predict likelihood of T21. The mathematics to create the algorithm is well known and not proprietary. Such an algorithm for predicting likelihood of T21 can be run on a computing system, and may be configured as software and/or or hardware. Data can be input into the computing system in order to operate and optimize the T21 prediction algorithm.
  • the results of a subject's diagnosis (T21) or the information of the Group of the combination of biomarkers, screening, prognosis or monitoring is typically displayed or provided to a user such as a clinician, health care worker or other caregiver, laboratory personnel or the patient.
  • the results may be quantitative information (e.g. the level or amount of a marker compared to a control) or qualitative information (e.g. diagnosis of spontaneous preterm birth) for all biomarkers in the defined Group.
  • the output can comprise guidelines or instructions for interpreting the results, for example, numerical or other limits that indicate the presence or absence of T21.
  • the guidelines may also specify the diagnosis, for example whether there is a high risk of T21.
  • the output can include tools for interpreting the results to arrive at a diagnosis, prognosis or treatment plan, for example, an output may include ranges or cut-offs for abnormal or normal status to arrive at a diagnosis, prognosis, or treatment plan or further diagnostic confirmation procedure.
  • the output can also provide a recommended therapeutic plan, and it may include other clinical information and guidelines and instructions for interpreting the information.
  • output devices can be used to transmit the results of a method of the invention.
  • output devices include without limitation, a visual output device (e.g. a computer screen or a printed paper), an auditory output device (e.g., a speaker), a printer or a patient s electronic medical record.
  • the format of the output providing the results and related information may be a visual output (e.g., paper or a display on a screen), a diagram such as a graph, chart or voltammetric trace, an audible output (e.g. a speaker) or, a numerical value.
  • the output is a numerical value, in particular the amount or relative amount of each biomarker of a specific combination of biomarkers in a subject's sample compared to a control.
  • the output is a graph that indicates a value, such as an amount or relative amount, of the at least one marker in the sample from the subject on a standard curve.
  • the output (such as a graphical output) shows or provides a cut-off value or level that indicates the presence of high risk of T21.
  • An output may be communicated to a user by physical, audible or electronic means, including mail, telephone, facsimile transmission, email or an electronic medical record.
  • the analytic methods described herein can be implemented by use of computer systems and methods described below and known in the art.
  • the invention provides computer readable media comprising one or more combinations of biomarkers, and optionally other markers (e.g. markers of T21).
  • “Computer readable media” refers to any medium that can be read and accessed directly by a computer.
  • the invention contemplates computer readable medium having recorded thereon markers identified for patients and controls.
  • “Recorded” refers to a process for storing information on computer readable medium. The skilled artisan can readily adopt any of the presently known methods for recording information on computer readable medium to generate manufactures comprising information on one or more combinations of biomarkers.
  • a variety of data processor programs and formats can be used to store information on one or more combinations of biomarkers, and other markers on computer readable medium. Any number of data processor structuring formats (e.g., text file or database) may be adapted in order to obtain computer readable medium having recorded thereon the marker information.
  • data processor structuring formats e.g., text file or database
  • biomarker information in computer readable form
  • one skilled in the art can use the information in computer readable form to compare marker information obtained during or following therapy with the information stored within the data storage means.
  • a system of the invention generally comprises a computer; a database server coupled to the computer; a database coupled to the database server having data stored therein, the data comprising records of data comprising one or more combinations of biomarkers, and a code mechanism for applying queries based upon a desired selection criteria to the data file in the database to produce reports of records which match the desired selection criteria.
  • the invention contemplates a method for determining whether a subject has T21comprising: (a) receiving phenotypic and/or clinical information on the subject and information on one or more combinations of biomarkers, associated with samples from the subject; (b) acquiring information from a network corresponding to the one or more combinations of biomarkers; and (c) based on the phenotypic information, information on one or more combinations of biomarkers, and optionally other markers, and acquired information, determining whether the subject has T21; and (d) optionally recommending a procedure or treatment.
  • RNAs After reordering potential marker RNAs by p value and narrowness of distribution, the 36 highest scoring exons representing 36 mRNAs (19 serendipitously originating from a gene on the #21 chromosome) and the 18 highest scoring small noncoding RNAs (including 1 originating from a gene on the #21 chromosome) were confirmed by q-PCR (Table 2). These 54 RNAs were then subject to Validation testing. These data confirm that the microarray analysis functioned as designed and identified RNAs that were informative of the trisomy 21 status of the fetus.
  • RNA is obtained using a process based on a phenol/guanidium isothiocyanate/glycerol phase separation.
  • RNA concentration was measured by using a Qubit® 2.0 Fluorometer (Life Technologies, Grand Island, NY) as recommended by the manufacturer. Briefly, calibration of the Qubit® 2.0 Fluorometer was done using Standard #1 and #2. Working solution was prepared by diluting the QubitTM RNA reagent at 1:200 in QubitTM RNA buffer. Working solution (190 ul) and 10 ul of standard or RNA sample were mixed, then incubate at room temperature for 2 minutes. The RNA concentration was determined.
  • mRNA RT The RNA samples were diluted, and a master mix prepared including dNTP mix, Omniscript Reverse Transcriptase and Random Primer (Invitrogen, Carlsbad CA). The mRNA of each sample was converted into cDNA at 37 °C for 60min per manufacturer instructions.
  • miRNA RT The miRs were polyadenylated using reagents from the Invitrogen NCode miRNA First-Strand cDNA Synthesis Kit (ThermoFisher). The polyadenylated microRNA was reverse transcribed to generate the first strand of cDNA according to the manufactory’s protocol.
  • Preamplification and qPCR Multiplex qPCR reactions were performed by SYBR green using the ViiA 7 Real-Time PCR System.
  • the primers for the gene panels were custom designed and synthesized by Integrated DNA Technologies (IDT, Coralville, IA).
  • the probe sets in each reaction well included primers for the biomarker, normalization, and spike genes so that all three genes were run in the same reaction well to minimize assay variation. Information about the primer sequences used is available from the authors.
  • Preamplification was performed, lul RT samples were prepared for the preamplification Mix Reaction and underwent 12 cycles.
  • Two customized probe-based microfluidic PCR Cards with 384 wells were developed for the selected mRNA and small noncoding RNA markers using a proprietary method (Rosetta Signaling Laboratory, Mission Hills, KS).
  • the probe sets in each well included primers for biomarker, normalization, and spike genes so that all three were run in the same reaction well to minimize assay variation.
  • One ul RT samples were prepared with the preamplification Mix Reaction and underwent 12 cycles.
  • Two ul preamplification cDNA samples were diluted into lOul PCR reaction mix, followed by RT PCR using SYBR Green Supermix (ThermoFisher). Threshold cycles (Ct values) of qPCR reactions were extracted using QuantStudioTM Software VI.3 (Applied Biosystems, Foster City CA).
  • Potential markers were normalized to housekeeping control sequences and to a spiked-in cDNA, the Cts determined and the relative expression calculated using the 2 -AACt method.
  • sample biological sample
  • biological sample means a material known or suspected of expressing or containing one or more combinations of biomarkers.
  • a test sample can be used directly as obtained from the source or following a pretreatment to modify the character of the sample.
  • a sample can be derived from any biological source, such as tissues, extracts, or cell cultures, including cells, cell lysates, and physiological fluids, such as, for example, whole blood, plasma, serum, saliva, ocular lens fluid, cerebral spinal fluid, sputum, sweat, urine, milk, ascites fluid, synovial fluid, peritoneal fluid, and the like.
  • a sample can be obtained from animals, preferably mammals, most preferably humans.
  • a sample can be treated prior to use, such as preparing plasma from blood, diluting viscous fluids, and the like.
  • Methods of treatment can involve filtration, distillation, extraction, concentration, inactivation of interfering components, the addition of reagents, and the like.
  • the experiments used plasma cell-free RNA from 20 women 11-13 wks tested by RNA and miRNA microarrays followed by qRT-PCR. Thirty-six mRNAs and 18 small RNAs were identified by qPCR of the Discovery cDNA as potential markers of embryonic T21. The second objective was validation of the RNA predictors in 998 independent pregnancies at 11-13 wks including 50 T21. Initial analyses identified 9-15 differentially expressed RNA with modest predictive power (AUC ⁇ 0.70). The 54 RNAs were subjected to machine learning. Eleven algorithms were trained on one partition and tested on an independent partition. The three best algorithms were identified by Kappa score and the effects of training/ testing partition size and dataset class imbalance on prediction evaluated. 6-10 RNAs predicted T21 with AUCs up to 1.00. The findings suggest a maternal sample at 11-13 wks tested by qRT-PCR and machine learning may accurately predict T21 but at a lower cost than DNA, thus opening the door to universal screening.
  • ML classification allowed for the first time the prediction of embryonic T21 using a minimally invasive maternal sample collected at 11-13 wks. The improvement in accuracy over our earlier effort was dramatic, yielding algorithms with predicted AUCs up to 1.00. Just as important, the approach permitted test simplification, reducing the number of RNA markers down from the original 54 to a more manageable number. In retrospect, we found that many of the prospective biomarker RNAs were highly correlated (supplemental Table 4). It is likely that this reduces the efficiency of ML based variable selection, and a refinement of the biomarker list to include variables with low correlation might further improve ML classification.
  • the heteroscedastic nature of qPCR and qRT-PCR data are concerns for regression analysis, analysis of variance, and machine learning methods that assume a linear relationship between independent and dependent variables. Decision tree methods, support vector machine, naive Bayes, and regression machine learning methods were screened here because they are less sensitive to these features.
  • Classification by ML employs mathematical tools to predict class, e.g., case or control, and, as such, is a branch of artificial intelligence.
  • One advantage of ML is it lacks underlying predispositions or user biases. It uses numerical methods to identify salient features, or, in this instance, RNAs predictive of T21. Importantly, large data sets can be rendered tractable through the application of ML. Generally, those datasets number in the tens or hundreds of thousand samples. Here, the use of one thousand samples is still on the “low end” of ML’s powerband and a larger dataset could improve ML modeling.
  • ML methods may be affected by imbalanced datasets. We found improved performance applying two methods that specifically address class imbalance. In addition to the impact of dataset size and class imbalance, ML is subject to overfitting, which means our predictive Accuracy and Kappa values may be overly optimistic.
  • ML has proven robust and efficient at “mining”, e.g., extracting salient features from large datasets.
  • tree-based ML algorithms are not strongly affected by the lack of normality or constant variance as is characteristic of qPCR and other genomic datasets, in contrast to linear regression or ANOVA methods statistical-inference based upon homoscedastic, normality and unimodal data assumptions. While we posited that tree-based methods might be most useful here, there are no a priori rules to prospectively identify optimal ML algorithms.
  • the CARET package in R contains more than 130 ML algorithms to evaluate, some are regression-based, and must be modified for classification. Here, we employed a simplified workflow and sampled 11 of these 130 algorithms.
  • ML used some, but not all of the RNAs found to be differentially expressed.
  • Var 27 ERG fusion gene was found to be differentially expressed after FDR correction via Q-Values and Benjamini-Hochberg method. This variable was not found as an important variable in any of the ML models shown.
  • ML identified some important predictors variables that were not differentially expressed as important ones, e.g, Var 54. GART. Since ML uses mathematical rather than statistical methods to learn and predict class, it is interesting ML independently identified many chromosome #21 and differentially expressed RNAs as important predictors. In the future, it might be valuable to prioritize markers by clustering via gene ontology, pathway or Bayesian-like Convergent Functional Genomics approach.
  • Table 6 shows the variable for the GBM model (up.gbm) and 70% training thereof, which shows the accuracy and kappa.
  • Table 7 shows the variable for the GBM model (up.gbm) and 75% training thereof, which shows the accuracy and kappa.
  • Table 8 shows the variable for the GBM model (orig.gbm) and 75% training thereof, which shows the accuracy and kappa.
  • Table 9 shows the variable for the C50 model (orig.C50) and 80% training thereof, which shows the accuracy and kappa.
  • Table 10 shows the variable for the RF model (up.RF) and 80% training thereof, which shows the accuracy and kappa.
  • Table 11 shows the variable for the RF model (orig.RF) and 80% training thereof, which shows the accuracy and kappa.
  • Machine learning can include Deep neural networks (DNNs), which are computer system architectures that have recently been created for complex data processing and artificial intelligence (AI).
  • DNNs are machine learning models that employ more than one hidden layer of nonlinear computational units to predict outputs for a set of received inputs.
  • DNNs can be provided in various configurations for various purposes, and continue to be developed to improve performance and predictive ability.
  • the models recited herein can be trained as shown in the Tables to arrive at the machine learning model.
  • a unique segment of a sequence in a sequence listing is a specific sequence segment that is found within the recited sequence of the SEQ ID NO, and substantially absent in the rest of the RNA transciptome. That is, the unique segment of the sequence in the Sequence Listing identified by the SEQ ID NO can be used as a probe or a primer that is specific for that SEQ ID NO.
  • the techniques available for identifying a primer or a probe available to one of ordinary skill in the art can be used to identify one or more unique segments of each SEQ ID NO recited in the Sequence Listing.

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Abstract

L'invention concerne des procédés de détection d'un groupe de biomarqueurs. Le profil de traduction du groupe de biomarqueurs peut être utilisé pour déterminer si un sujet, tel qu'un fœtus, présente une trisomie 21. Les procédés comprennent la détection d'un ou de plusieurs groupes spécifiques de biomarqueurs dans un échantillon biologique, et la détermination quant à savoir si l'expression des biomarqueurs est modifiée par rapport à l'expression des biomarqueurs chez un ou plusieurs sujets qui n'ont pas de trisomie 21 (par exemple une norme transcriptionnelle). L'échantillon biologique peut être un échantillon de sang et les biomarqueurs sont des ARN plasmatiques acellulaires.
EP22771947.3A 2021-03-16 2022-03-10 Combinaisons de biomarqueurs pour des procédés de détection de la trisomie 21 Pending EP4308719A4 (fr)

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US17/203,534 US12474355B2 (en) 2011-12-01 2021-03-16 Combinations of biomarkers for methods for detecting trisomy 21
PCT/US2022/019680 WO2022197516A1 (fr) 2021-03-16 2022-03-10 Combinaisons de biomarqueurs pour des procédés de détection de la trisomie 21

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AU2003263660A1 (en) * 2003-08-29 2005-03-16 Pantarhei Bioscience B.V. Prenatal diagnosis of down syndrome by detection of fetal rna markers in maternal blood
CA3147058A1 (fr) * 2005-03-18 2006-09-21 The Chinese University Of Hong Kong Marqueurs de diagnostic prenatal, de surveillance ou de prediction de lapreeclampsie
US20150038358A1 (en) * 2011-12-01 2015-02-05 University Of Kansas Methods for detecting trisomy 21
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